{"id":109840,"date":"2026-07-10T11:00:52","date_gmt":"2026-07-10T09:00:52","guid":{"rendered":"https:\/\/brand24.com\/blog\/?p=109840"},"modified":"2026-07-14T12:51:58","modified_gmt":"2026-07-14T10:51:58","slug":"sentiment-analysis","status":"publish","type":"post","link":"https:\/\/brand24.com\/blog\/sentiment-analysis\/","title":{"rendered":"Sentiment Analysis in 2026: Definition, AI Methods &amp; Original Research"},"content":{"rendered":"\n<p><strong>85% of consumers <\/strong>are <em>more likely<\/em> to choose a business after reading positive reviews, while <strong>77%<\/strong> say negative reviews make them think twice (BrightLocal, 2026).<\/p>\n\n\n\n<p>To find out what sentiment analysis looks like in practice in 2026, I analyzed <strong>12,894 online mentions<\/strong> using Brand24&#8217;s AI Brand Assistant.<\/p>\n\n\n\n<p>This guide shares everything I learned during this research.<\/p>\n\n\n<style>.acf-key-takeaways__heading{padding:22px 30px 20px;margin:0;font-weight:600 !important;display:inline-flex;align-items:center;gap:1.1875rem;border:1px solid #c3e1d2;border-bottom:none;border-top-left-radius:1.25rem;border-top-right-radius:1.25rem}@media(min-width: 768px){.acf-key-takeaways__heading{padding:22px 40px 20px;gap:1.4375rem}}.acf-key-takeaways__icon{width:1.625rem;height:1.625rem;background-color:#9cbfaf;border-radius:50%;display:flex;align-items:center;justify-content:center}.acf-key-takeaways__list{border:1px solid #c3e1d2;border-top-right-radius:1.25rem;border-bottom-right-radius:1.25rem;border-bottom-left-radius:1.25rem;margin:0;padding:0;list-style:none;overflow:hidden}.acf-key-takeaways__item{padding:28px 34px 28px 61px;background-color:#e8f4ee;margin:0;border-bottom:1px solid #c3e1d2;position:relative}@media(min-width: 768px){.acf-key-takeaways__item{padding:28px 54px 28px 81px}}.acf-key-takeaways__item::before{content:\"\";position:absolute;top:35px;left:28px;width:.75rem;height:.75rem;background-color:#9cbfaf;border-radius:50%}@media(min-width: 768px){.acf-key-takeaways__item::before{top:39px;left:40px}}.acf-key-takeaways__item:nth-child(even){background-color:#dfefe7}.acf-key-takeaways__item:last-child{border-bottom:none}.acf-key-takeaways__title{font-weight:600 !important;margin-bottom:.625rem}.acf-key-takeaways__text{font-family:\"Inter\",sans-serif;font-size:16px;line-height:26px;margin:0}@media(min-width: 768px){.acf-key-takeaways__text{font-size:18px;line-height:30px}}.single-post-content__content .acf-key-takeaways__heading{font-family:\"Inter\",sans-serif;font-size:16px;line-height:26px}@media(min-width: 768px){.single-post-content__content .acf-key-takeaways__heading{font-size:18px;line-height:30px}}.single-post-content__content .acf-key-takeaways__title{font-family:\"Inter\",sans-serif;font-size:16px;line-height:26px}@media(min-width: 768px){.single-post-content__content .acf-key-takeaways__title{font-size:18px;line-height:30px}}.single-post-content__content p.acf-key-takeaways__text{line-height:1.875rem}@media(max-width: 768px){.single-post-content__content p.acf-key-takeaways__text{font-size:1rem !important}}<\/style>    <div class=\"acf-key-takeaways\">\n        <p class=\"acf-key-takeaways__heading\">\n            <span class=\"acf-key-takeaways__icon\">\n                <svg width=\"10\" height=\"12\" viewBox=\"0 0 10 12\" fill=\"none\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\">\n                    <path d=\"M8.41177 0C8.8341 0 9.17647 0.34237 9.17647 0.764706V11.0882C9.17647 11.3821 9.00815 11.6501\n                8.74334 11.7775C8.47839 11.9049 8.16337 11.8693 7.93382 11.6857L4.58824 9.00919L1.24265 11.6857C1.01311\n                11.8693 0.698079 11.9049 0.433134 11.7775C0.168324 11.6501 0 11.3821 0 11.0882V0.764706C0 0.561893\n                0.0806248 0.367445 0.224035 0.224035C0.367445 0.0806248 0.561893 0 0.764706 0H8.41177ZM1.52941\n                9.49609L4.11029 7.43199C4.38958 7.20856 4.78689 7.20856 5.06618 7.43199L7.64706\n                9.49609V1.52941H1.52941V9.49609Z\" fill=\"black\" \/>\n                <\/svg>\n            <\/span>\n            Key takeaways:        <\/p>\n        <ul class=\"acf-key-takeaways__list\">\n                            <li class=\"acf-key-takeaways__item\">\n                    <p class=\"acf-key-takeaways__title\">What is sentiment analysis? Definition<\/p>\n                    <p class=\"acf-key-takeaways__text\">Sentiment analysis is an NLP technique that classifies online text as positive, negative, or neutral \u2014 and more advanced tools detect specific emotions (joy, anger, fear, disgust) and intent.<\/p>\n                <\/li>\n                            <li class=\"acf-key-takeaways__item\">\n                    <p class=\"acf-key-takeaways__title\">The conversation around sentiment analysis is massive<\/p>\n                    <p class=\"acf-key-takeaways__text\">Brand24&#039;s original research found 12,894 mentions of sentiment analysis generating 23.7M in reach in a single month (June\u2013July 2026), with Finance\/Trading and Marketing &amp; PR dominating the discussion.<\/p>\n                <\/li>\n                            <li class=\"acf-key-takeaways__item\">\n                    <p class=\"acf-key-takeaways__title\">AI sentiment analysis uses machine learning or hybrid models<\/p>\n                    <p class=\"acf-key-takeaways__text\">They process far more data than any human team could manually review, with leading tools reaching 85\u201392% accuracy \u2014 though accuracy alone isn&#039;t the full picture.<\/p>\n                <\/li>\n                            <li class=\"acf-key-takeaways__item\">\n                    <p class=\"acf-key-takeaways__title\">The biggest challenge in sentiment analysis is interpretation<\/p>\n                    <p class=\"acf-key-takeaways__text\">Sentiment models still misclassify nuanced content (sarcasm, cultural slang, irony) up to 35% of the time, making human review part of a responsible workflow.<\/p>\n                <\/li>\n                            <li class=\"acf-key-takeaways__item\">\n                    <p class=\"acf-key-takeaways__title\">What is the most effective approach to sentiment analysis?<\/p>\n                    <p class=\"acf-key-takeaways__text\">One of the most effective approaches is the Brand24 Sentiment Intelligence Framework: a a five-step cycle of target, listen, decode, act, and measure, turning raw sentiment data into decisions that improve customer experience and protect brand reputation.<\/p>\n                <\/li>\n                    <\/ul>\n    <\/div>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"what-is\"><strong>What is sentiment analysis?<\/strong><\/h2>\n\n\n\n<p class=\"has-background\" style=\"background-color:#e8f4ee\"><strong>Sentiment analysis<\/strong> is a natural language processing (NLP) technique for determining the emotional tone behind text, speech, or other forms of communication. <br><br>The goal is to understand whether people express positive, negative, or neutral feelings about a brand, product, person, or topic.<\/p>\n\n\n\n<p><strong>In simple terms:<\/strong>&nbsp;It&#8217;s a technique that helps you understand how people feel when they express themselves online.<\/p>\n\n\n\n<p><strong>Let&#8217;s see how it works in practice:<\/strong><\/p>\n\n\n<style>.wp-block-table.is-style-comparison-table{text-align:left;border:1px solid #d4e5dc;border-radius:16px;overflow:hidden;overflow-x:auto}.wp-block-table.is-style-comparison-table thead{border-bottom:none}.wp-block-table.is-style-comparison-table tfoot{border-top:none}.wp-block-table.is-style-comparison-table table{width:100%;min-width:582px;margin:0;border:none;border-collapse:collapse}.wp-block-table.is-style-comparison-table th,.wp-block-table.is-style-comparison-table td{padding:14px 20px;font-size:14px;line-height:18px;border:none;border-bottom:1px solid #d4e5dc;border-right:1px solid #d4e5dc}.wp-block-table.is-style-comparison-table th:last-child,.wp-block-table.is-style-comparison-table td:last-child{border-right:none}.wp-block-table.is-style-comparison-table th p,.wp-block-table.is-style-comparison-table td p{font-size:14px !important;line-height:18px;margin-bottom:0}.wp-block-table.is-style-comparison-table th strong,.wp-block-table.is-style-comparison-table td strong{font-weight:700}.wp-block-table.is-style-comparison-table th,.wp-block-table.is-style-comparison-table tfoot tr{font-size:16px;line-height:30px;font-weight:700;text-align:left;background:none}@media(max-width: 768px){.wp-block-table.is-style-comparison-table th,.wp-block-table.is-style-comparison-table tfoot tr{font-size:14px !important;line-height:18px !important}}.wp-block-table.is-style-comparison-table tbody tr:nth-child(even){background-color:#e8f4ee}.wp-block-table.is-style-comparison-table tbody tr:last-child td{border-bottom:none}.wp-block-table.is-style-comparison-table td img{display:block;max-width:91px;height:auto;margin-bottom:8px;margin-left:unset;margin-right:unset;margin-top:8px}.wp-block-table.is-style-comparison-table td img:first-of-type{margin-top:0}.wp-block-table.is-style-comparison-table .has-text-align-center{text-align:center}.wp-block-table.is-style-comparison-table .has-text-align-right{text-align:right}.wp-block-table.is-style-comparison-table .has-text-align-left{text-align:left}.wp-block-table.is-style-comparison-table td a{font-weight:400 !important;text-decoration:underline !important}.wp-block-table.is-style-comparison-table td a:hover{text-decoration:none !important}.wp-block-table.has-row-numbers thead th:first-child,.wp-block-table.has-row-numbers tbody td:first-child,.wp-block-table.has-row-numbers tfoot td:first-child{padding-left:70px}.wp-block-table.has-row-numbers tbody{counter-reset:comparison-table-row}.wp-block-table.has-row-numbers tbody td:first-child{position:relative}.wp-block-table.has-row-numbers tbody td:first-child::before{counter-increment:comparison-table-row;content:counter(comparison-table-row);position:absolute;left:20px;top:50%;transform:translateY(-50%);display:inline-flex;align-items:center;justify-content:center;width:32px;height:32px;border-radius:16px;background-color:#cbe7d9;font-size:14px;line-height:1em;font-weight:700}<\/style>\n<figure class=\"wp-block-table has-row-numbers is-style-comparison-table\"><table class=\"has-fixed-layout\"><thead><tr><th>Phase<\/th><th>What it does<\/th><\/tr><\/thead><tbody><tr><td><strong>Data collection<\/strong><\/td><td>The tool starts by monitoring multiple online sources.<\/td><\/tr><tr><td><strong>Natural Language Processing (NLP)<\/strong><\/td><td>NLP algorithms analyze the text structure, context, and meaning.<\/td><\/tr><tr><td><strong>Sentiment classification<\/strong><\/td><td>Machine learning models or rule-based methods classify the sentiment.<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n<p>In practice, <a href=\"https:\/\/brand24.com\/blog\/best-sentiment-analysis-tools\/\" target=\"_blank\" rel=\"noopener\" title=\"\">sentiment analysis tools<\/a> automatically scan online mentions and assign them a sentiment score:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Positive sentiment<\/strong>: <em>&#8220;I love how fast their customer support responded.&#8221;<\/em><\/li>\n\n\n\n<li><strong>Neutral sentiment<\/strong>: <em>&#8220;They released a new feature update in June.&#8221;<\/em><\/li>\n\n\n\n<li><strong>Negative sentiment<\/strong>: <em>&#8220;Been waiting three days for a reply. This is ridiculous.&#8221;<\/em><\/li>\n<\/ul>\n\n\n\n<figure data-wp-context=\"{&quot;imageId&quot;:&quot;6a5a28f5db5ef&quot;}\" data-wp-interactive=\"core\/image\" data-wp-key=\"6a5a28f5db5ef\" class=\"wp-block-image aligncenter size-full wp-lightbox-container\"><img loading=\"lazy\" decoding=\"async\" width=\"1000\" height=\"946\" data-wp-class--hide=\"state.isContentHidden\" data-wp-class--show=\"state.isContentVisible\" data-wp-init=\"callbacks.setButtonStyles\" data-wp-on--click=\"actions.showLightbox\" data-wp-on--load=\"callbacks.setButtonStyles\" data-wp-on-window--resize=\"callbacks.setButtonStyles\" src=\"https:\/\/brand24.com\/blog\/app\/uploads\/2025\/09\/Screenshot-2026-07-13-at-05.51.40-1.png\" alt=\"\" class=\"wp-image-184770\" srcset=\"https:\/\/brand24.com\/blog\/app\/uploads\/2025\/09\/Screenshot-2026-07-13-at-05.51.40-1.png 1000w, https:\/\/brand24.com\/blog\/app\/uploads\/2025\/09\/Screenshot-2026-07-13-at-05.51.40-1-13x12.png 13w, https:\/\/brand24.com\/blog\/app\/uploads\/2025\/09\/Screenshot-2026-07-13-at-05.51.40-1-300x284.png 300w, https:\/\/brand24.com\/blog\/app\/uploads\/2025\/09\/Screenshot-2026-07-13-at-05.51.40-1-168x159.png 168w, https:\/\/brand24.com\/blog\/app\/uploads\/2025\/09\/Screenshot-2026-07-13-at-05.51.40-1-90x85.png 90w\" sizes=\"auto, (max-width: 1000px) 100vw, 1000px\" \/><button\n\t\t\tclass=\"lightbox-trigger\"\n\t\t\ttype=\"button\"\n\t\t\taria-haspopup=\"dialog\"\n\t\t\taria-label=\"Enlarge\"\n\t\t\tdata-wp-init=\"callbacks.initTriggerButton\"\n\t\t\tdata-wp-on--click=\"actions.showLightbox\"\n\t\t\tdata-wp-style--right=\"state.imageButtonRight\"\n\t\t\tdata-wp-style--top=\"state.imageButtonTop\"\n\t\t>\n\t\t\t<svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"12\" height=\"12\" fill=\"none\" viewBox=\"0 0 12 12\">\n\t\t\t\t<path fill=\"#fff\" d=\"M2 0a2 2 0 0 0-2 2v2h1.5V2a.5.5 0 0 1 .5-.5h2V0H2Zm2 10.5H2a.5.5 0 0 1-.5-.5V8H0v2a2 2 0 0 0 2 2h2v-1.5ZM8 12v-1.5h2a.5.5 0 0 0 .5-.5V8H12v2a2 2 0 0 1-2 2H8Zm2-12a2 2 0 0 1 2 2v2h-1.5V2a.5.5 0 0 0-.5-.5H8V0h2Z\" \/>\n\t\t\t<\/svg>\n\t\t<\/button><figcaption class=\"wp-element-caption\">Examples of positive, neutral, and negative online mentions<\/figcaption><\/figure>\n\n\n\n<p><strong>A real-life example of sentiment analysis:<\/strong><\/p>\n\n\n<style>.acf-numeric-list__list{list-style:none;padding:0;margin:0}.acf-numeric-list__item{display:grid;grid-template-columns:1.875rem 1fr;grid-template-rows:1fr;align-items:center;gap:1.5625rem;margin-bottom:.9375rem}.acf-numeric-list__item:last-child{margin-bottom:0}.acf-numeric-list__number{background-color:#00ef88;color:#000;border-radius:50%;width:1.875rem;height:1.875rem;display:flex;align-items:center;justify-content:center;font-weight:600}<\/style><div class=\"acf-numeric-list\">\n    <ul class=\"acf-numeric-list__list\">\n                    <li class=\"acf-numeric-list__item\">\n                <span class=\"acf-numeric-list__number\">1<\/span>\n                <span class=\"acf-numeric-list__text\">When Maciej Moc, Marketing Director at Pasibus, first integrated sentiment analysis into their daily marketing workflow, he wasn&#039;t expecting it to change how they approached their entire content strategy.<\/span>\n            <\/li>\n                    <li class=\"acf-numeric-list__item\">\n                <span class=\"acf-numeric-list__number\">2<\/span>\n                <span class=\"acf-numeric-list__text\">But it did! For three years in a row, they made AVE (Advertising Value Equivalency) a key annual marketing KPI.<\/span>\n            <\/li>\n                    <li class=\"acf-numeric-list__item\">\n                <span class=\"acf-numeric-list__number\">3<\/span>\n                <span class=\"acf-numeric-list__text\">Over time, the team saw a clear feedback loop: tracking sentiment pushed them to keep improving how they communicated, and that led to real, measurable results.<\/span>\n            <\/li>\n            <\/ul>\n<\/div>\n\n\n<style>.acf-testimonial{padding:40px 30px;background-color:#e8f4ee;border-radius:20px;max-width:640px;margin-left:auto;margin-right:auto}@media(min-width: 768px){.acf-testimonial{padding:62px 91px}}.acf-testimonial__logos{margin-bottom:20px}@media(min-width: 768px){.acf-testimonial__logos{margin-bottom:36px}}.acf-testimonial__question{font-family:\"Inter\",sans-serif;font-size:20px;line-height:28px;font-weight:700;margin-bottom:15px;max-width:450px}@media(min-width: 768px){.acf-testimonial__question{font-size:24px;line-height:32px}}@media(min-width: 768px){.acf-testimonial__question{margin-bottom:25px}}.acf-testimonial__answer{font-family:\"Inter\",sans-serif;font-size:16px;line-height:26px;margin-bottom:36px}@media(min-width: 768px){.acf-testimonial__answer{font-size:18px;line-height:30px}}@media(min-width: 576px){.acf-testimonial__answer{margin-bottom:60px}}.acf-testimonial__answer:last-child{margin-bottom:0}@media(min-width: 576px){.acf-testimonial__row{display:flex;gap:25px;align-items:center}}.acf-testimonial__author-image{width:60px;height:60px;border-radius:50%;overflow:hidden;flex-shrink:0;margin-bottom:10px;background-color:#c2dcce}@media(min-width: 768px){.acf-testimonial__author-image{width:80px;height:80px;margin-bottom:0}}.acf-testimonial__author-image img{width:100%;height:100%;object-fit:cover}.acf-testimonial__author-name{font-size:16px;line-height:140%;font-weight:700;margin-bottom:4px}@media(min-width: 768px){.acf-testimonial__author-name{font-size:18px;line-height:140%}}.acf-testimonial__author-linkedin{display:inline-block;position:relative;top:-4px;margin-left:8px}.acf-testimonial__author-position{font-size:16px;line-height:100%}@media(min-width: 768px){.acf-testimonial__author-position{font-size:18px}}.acf-testimonial__button{margin-top:30px;flex-shrink:0;border-radius:30px;padding:11px 21px;font-size:14px;line-height:18px;font-weight:500 !important;color:#000 !important;letter-spacing:-0.14px;background-color:#00ef88;border:none;transition:background-color .3s ease,opacity .3s ease;display:inline-block}@media(min-width: 768px){.acf-testimonial__button{margin-top:60px}}.acf-testimonial__button:hover{background-color:#4bffae;text-decoration:none;opacity:.9}.acf-testimonial__button:focus-visible{outline:2px solid #00ef88}.acf-testimonial--primary{background-color:#00ef88}.acf-testimonial--primary .acf-testimonial__question,.acf-testimonial--primary .acf-testimonial__answer,.acf-testimonial--primary .acf-testimonial__author-name,.acf-testimonial--primary .acf-testimonial__author-position{color:#000}.acf-testimonial--primary .acf-testimonial__button{background-color:#000;color:#fff !important;transition:background-color .3s ease-in-out}.acf-testimonial--primary .acf-testimonial__button:hover{background-color:#171717}.acf-testimonial--violet{background-color:#000}.acf-testimonial--violet .acf-testimonial__question,.acf-testimonial--violet .acf-testimonial__answer,.acf-testimonial--violet .acf-testimonial__author-name,.acf-testimonial--violet .acf-testimonial__author-position{color:#fff}.acf-testimonial--violet .acf-testimonial__author-image{background-color:#22272a}.acf-testimonial--violet .acf-testimonial__logo--b24 svg path,.acf-testimonial--violet .acf-testimonial__separator svg path{fill:#fff}.acf-testimonial--violet .acf-testimonial__button{background-color:#bf00ff;color:#000 !important;transition:background-color .3s ease-in-out}.acf-testimonial--violet .acf-testimonial__button:hover{background-color:#bf00ff}<\/style><div class=\"acf-testimonial acf-testimonial--default\">\n                    <div class=\"acf-testimonial__answer\">The Advertising Value Equivalency metric has been part of our annual marketing KPIs for at least three years, driving us to ensure our content is viral and engaging. Monitoring this metric essentially compels us to continuously improve the quality of our communication, which directly translates into tangible results.\r\n<\/div>\n        <div class=\"acf-testimonial__row\">\n                    <div class=\"acf-testimonial__author-image\">\n                <img decoding=\"async\" width=\"105\" height=\"105\" src=\"https:\/\/brand24.com\/blog\/app\/uploads\/2025\/09\/Maciej-Moc-pasibus-1.webp\" class=\"attachment-thumbnail size-thumbnail\" alt=\"\" loading=\"lazy\" srcset=\"https:\/\/brand24.com\/blog\/app\/uploads\/2025\/09\/Maciej-Moc-pasibus-1.webp 105w, https:\/\/brand24.com\/blog\/app\/uploads\/2025\/09\/Maciej-Moc-pasibus-1-12x12.webp 12w, https:\/\/brand24.com\/blog\/app\/uploads\/2025\/09\/Maciej-Moc-pasibus-1-60x60.webp 60w, https:\/\/brand24.com\/blog\/app\/uploads\/2025\/09\/Maciej-Moc-pasibus-1-64x64.webp 64w, https:\/\/brand24.com\/blog\/app\/uploads\/2025\/09\/Maciej-Moc-pasibus-1-48x48.webp 48w, https:\/\/brand24.com\/blog\/app\/uploads\/2025\/09\/Maciej-Moc-pasibus-1-42x42.webp 42w, https:\/\/brand24.com\/blog\/app\/uploads\/2025\/09\/Maciej-Moc-pasibus-1-90x90.webp 90w, https:\/\/brand24.com\/blog\/app\/uploads\/2025\/09\/Maciej-Moc-pasibus-1-80x80.webp 80w\" sizes=\"auto, (max-width: 105px) 100vw, 105px\" \/>            <\/div>\n                <div class=\"acf-testimonial__author-content\">\n                            <div class=\"acf-testimonial__author-name\">Maciej Moc                            <\/div>\n                                        <div class=\"acf-testimonial__author-position\">Marketing Director @ Pasibus<\/div>\n                    <\/div>\n    <\/div>\n    <\/div>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"what-is-ai\">What is AI sentiment analysis?<\/h2>\n\n\n\n<p class=\"has-background\" style=\"background-color:#e8f4ee\"><strong>AI sentiment analysis<\/strong> is sentiment analysis powered by machine learning, deep learning, or large language models (LLMs), rather than simple rule-based word lists.<\/p>\n\n\n\n<p>A quick comparison table:<\/p>\n\n\n\n<figure class=\"wp-block-table is-style-comparison-table\"><table><thead><tr><th>Aspect of sentiment analysis<\/th><th>Traditional (rule-based)<\/th><th>AI-powered<\/th><\/tr><\/thead><tbody><tr><td><strong>How it classifies<\/strong><\/td><td>\ud83d\udccb Counts the positive and negative words from a <strong>predefined lexicon<\/strong><\/td><td>\ud83e\udd16 Learns from millions of labeled text examples to <strong>identify patterns<\/strong><\/td><\/tr><tr><td><strong>Sarcasm &amp; irony<\/strong><\/td><td>\u274c Misses it entirely<\/td><td>\u2705 Detects it <em>(with some limitations: see <a href=\"#top-challenges\" title=\"\">challenges<\/a> section)<\/em><\/td><\/tr><tr><td><strong>Languages<\/strong><\/td><td>\ud83c\udf10 Usually 1\u20132<\/td><td>\ud83c\udf0d 100+ <em>(For example, Brand24 supports over 100 languages using PLMs)<\/em><\/td><\/tr><tr><td><strong>Volume<\/strong><\/td><td>\u26a0\ufe0f Limited (breaks down at scale)<\/td><td>\u2705 Handles millions of mentions in real time<\/td><\/tr><tr><td><strong>Accuracy<\/strong><\/td><td>\ud83d\udcc9 ~60\u201370%<\/td><td>\ud83d\udcc8 85\u201392% on standard benchmarks<\/td><\/tr><tr><td><strong>Explainability<\/strong><\/td><td>\ud83d\udd0d High (you can see the rules)<\/td><td>\ud83d\udd12 Lower (often a &#8220;black box&#8221;)<\/td><\/tr><tr><td><strong>Best for<\/strong><\/td><td>Small, controlled datasets with predictable language<\/td><td>Real-world brand monitoring, social media, multilingual markets<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n<p>More advanced <strong>AI sentiment analysis<\/strong> goes beyond this three-way split to detect:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Specific emotions: <\/strong>joy, anger, fear, sadness, disgust, admiration<\/li>\n\n\n\n<li>Sarcasm and irony<\/li>\n\n\n\n<li><strong>Customer intent: <\/strong>complaint, praise, suggestion, purchase interest<\/li>\n\n\n\n<li><strong>Aspect-level sentiment: <\/strong>what specifically (product quality, pricing, support, etc.) is positive or negative<\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"how-to-use\">How to use AI for sentiment analysis<\/h3>\n\n\n\n<p>You don&#8217;t need to build or train a model yourself. Here&#8217;s how to use AI sentiment analysis practically in a sentiment analysis tool:<\/p>\n\n\n<div class=\"acf-numeric-list\">\n    <ul class=\"acf-numeric-list__list\">\n                    <li class=\"acf-numeric-list__item\">\n                <span class=\"acf-numeric-list__number\">1<\/span>\n                <span class=\"acf-numeric-list__text\">Set up a project with your brand name, product names, campaign hashtags, and key misspellings as tracking keywords.<\/span>\n            <\/li>\n                    <li class=\"acf-numeric-list__item\">\n                <span class=\"acf-numeric-list__number\">2<\/span>\n                <span class=\"acf-numeric-list__text\">Read the sentiment dashboard. The Analysis Tab shows the breakdown of positive, negative, and neutral mentions as both raw numbers and percentages<\/span>\n            <\/li>\n                    <li class=\"acf-numeric-list__item\">\n                <span class=\"acf-numeric-list__number\">3<\/span>\n                <span class=\"acf-numeric-list__text\">Go deeper with emotion analysis. Features like AI Emotion Analysis identify the dominant emotion behind each mention<\/span>\n            <\/li>\n                    <li class=\"acf-numeric-list__item\">\n                <span class=\"acf-numeric-list__number\">4<\/span>\n                <span class=\"acf-numeric-list__text\">Use Topic Analysis to see which topics drive sentiment changes in online discussions.<\/span>\n            <\/li>\n                    <li class=\"acf-numeric-list__item\">\n                <span class=\"acf-numeric-list__number\">5<\/span>\n                <span class=\"acf-numeric-list__text\">Set up real-time alerts for sudden drops in positive sentiment or spikes in negative mentions. <\/span>\n            <\/li>\n                    <li class=\"acf-numeric-list__item\">\n                <span class=\"acf-numeric-list__number\">6<\/span>\n                <span class=\"acf-numeric-list__text\">Use the AI Brand Assistant for deeper research questions \u2014 like understanding what the entire conversation about your industry looks like, not just your brand.<\/span>\n            <\/li>\n            <\/ul>\n<\/div>\n\n\n\n<figure data-wp-context=\"{&quot;imageId&quot;:&quot;6a5a28f5dd2aa&quot;}\" data-wp-interactive=\"core\/image\" data-wp-key=\"6a5a28f5dd2aa\" class=\"wp-block-image size-large wp-lightbox-container\"><img loading=\"lazy\" decoding=\"async\" width=\"1140\" height=\"747\" data-wp-class--hide=\"state.isContentHidden\" data-wp-class--show=\"state.isContentVisible\" data-wp-init=\"callbacks.setButtonStyles\" data-wp-on--click=\"actions.showLightbox\" data-wp-on--load=\"callbacks.setButtonStyles\" data-wp-on-window--resize=\"callbacks.setButtonStyles\" src=\"https:\/\/brand24.com\/blog\/app\/uploads\/2025\/09\/sentiment-analysis-brand-assistant-1-1140x747.png\" alt=\"\" class=\"wp-image-184777\" srcset=\"https:\/\/brand24.com\/blog\/app\/uploads\/2025\/09\/sentiment-analysis-brand-assistant-1-1140x747.png 1140w, https:\/\/brand24.com\/blog\/app\/uploads\/2025\/09\/sentiment-analysis-brand-assistant-1-18x12.png 18w, https:\/\/brand24.com\/blog\/app\/uploads\/2025\/09\/sentiment-analysis-brand-assistant-1-300x197.png 300w, https:\/\/brand24.com\/blog\/app\/uploads\/2025\/09\/sentiment-analysis-brand-assistant-1-243x159.png 243w, https:\/\/brand24.com\/blog\/app\/uploads\/2025\/09\/sentiment-analysis-brand-assistant-1-90x59.png 90w, https:\/\/brand24.com\/blog\/app\/uploads\/2025\/09\/sentiment-analysis-brand-assistant-1.png 1200w\" sizes=\"auto, (max-width: 1140px) 100vw, 1140px\" \/><button\n\t\t\tclass=\"lightbox-trigger\"\n\t\t\ttype=\"button\"\n\t\t\taria-haspopup=\"dialog\"\n\t\t\taria-label=\"Enlarge\"\n\t\t\tdata-wp-init=\"callbacks.initTriggerButton\"\n\t\t\tdata-wp-on--click=\"actions.showLightbox\"\n\t\t\tdata-wp-style--right=\"state.imageButtonRight\"\n\t\t\tdata-wp-style--top=\"state.imageButtonTop\"\n\t\t>\n\t\t\t<svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"12\" height=\"12\" fill=\"none\" viewBox=\"0 0 12 12\">\n\t\t\t\t<path fill=\"#fff\" d=\"M2 0a2 2 0 0 0-2 2v2h1.5V2a.5.5 0 0 1 .5-.5h2V0H2Zm2 10.5H2a.5.5 0 0 1-.5-.5V8H0v2a2 2 0 0 0 2 2h2v-1.5ZM8 12v-1.5h2a.5.5 0 0 0 .5-.5V8H12v2a2 2 0 0 1-2 2H8Zm2-12a2 2 0 0 1 2 2v2h-1.5V2a.5.5 0 0 0-.5-.5H8V0h2Z\" \/>\n\t\t\t<\/svg>\n\t\t<\/button><figcaption class=\"wp-element-caption\">An example of how to use an AI-powered Brand Assistant to analyze brand sentiment (Source: Brand24 tool)<\/figcaption><\/figure>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"what-are-methods\">What are sentiment analysis methods?<\/h2>\n\n\n\n<p>Sentiment analysis is a family of techniques, each designed to answer a slightly different question. <\/p>\n\n\n\n<figure data-wp-context=\"{&quot;imageId&quot;:&quot;6a5a28f5dd844&quot;}\" data-wp-interactive=\"core\/image\" data-wp-key=\"6a5a28f5dd844\" class=\"wp-block-image size-large wp-lightbox-container\"><img loading=\"lazy\" decoding=\"async\" width=\"1140\" height=\"1011\" data-wp-class--hide=\"state.isContentHidden\" data-wp-class--show=\"state.isContentVisible\" data-wp-init=\"callbacks.setButtonStyles\" data-wp-on--click=\"actions.showLightbox\" data-wp-on--load=\"callbacks.setButtonStyles\" data-wp-on-window--resize=\"callbacks.setButtonStyles\" src=\"https:\/\/brand24.com\/blog\/app\/uploads\/2025\/09\/sentiment-analysis-methods-image-1140x1011.png\" alt=\"\" class=\"wp-image-184780\" srcset=\"https:\/\/brand24.com\/blog\/app\/uploads\/2025\/09\/sentiment-analysis-methods-image-1140x1011.png 1140w, https:\/\/brand24.com\/blog\/app\/uploads\/2025\/09\/sentiment-analysis-methods-image-14x12.png 14w, https:\/\/brand24.com\/blog\/app\/uploads\/2025\/09\/sentiment-analysis-methods-image-300x266.png 300w, https:\/\/brand24.com\/blog\/app\/uploads\/2025\/09\/sentiment-analysis-methods-image-179x159.png 179w, https:\/\/brand24.com\/blog\/app\/uploads\/2025\/09\/sentiment-analysis-methods-image-90x80.png 90w, https:\/\/brand24.com\/blog\/app\/uploads\/2025\/09\/sentiment-analysis-methods-image.png 1280w\" sizes=\"auto, (max-width: 1140px) 100vw, 1140px\" \/><button\n\t\t\tclass=\"lightbox-trigger\"\n\t\t\ttype=\"button\"\n\t\t\taria-haspopup=\"dialog\"\n\t\t\taria-label=\"Enlarge\"\n\t\t\tdata-wp-init=\"callbacks.initTriggerButton\"\n\t\t\tdata-wp-on--click=\"actions.showLightbox\"\n\t\t\tdata-wp-style--right=\"state.imageButtonRight\"\n\t\t\tdata-wp-style--top=\"state.imageButtonTop\"\n\t\t>\n\t\t\t<svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"12\" height=\"12\" fill=\"none\" viewBox=\"0 0 12 12\">\n\t\t\t\t<path fill=\"#fff\" d=\"M2 0a2 2 0 0 0-2 2v2h1.5V2a.5.5 0 0 1 .5-.5h2V0H2Zm2 10.5H2a.5.5 0 0 1-.5-.5V8H0v2a2 2 0 0 0 2 2h2v-1.5ZM8 12v-1.5h2a.5.5 0 0 0 .5-.5V8H12v2a2 2 0 0 1-2 2H8Zm2-12a2 2 0 0 1 2 2v2h-1.5V2a.5.5 0 0 0-.5-.5H8V0h2Z\" \/>\n\t\t\t<\/svg>\n\t\t<\/button><\/figure>\n\n\n\n<p class=\"has-background\" style=\"background-color:#e8f4ee\">\ud83d\udca1 In my experience working with social listening data, <strong>knowing which type of sentiment analysis best matches your goal <\/strong>can save you a ton of unnecessary <a href=\"https:\/\/brand24.com\/blog\/what-is-media-monitoring-and-analysis\/\" target=\"_blank\" rel=\"noopener\" title=\"\">media monitoring<\/a> work.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"fine-grained\">1. Fine-grained sentiment analysis<\/h3>\n\n\n\n<h4 class=\"wp-block-heading\" id=\"what1\">\ud83d\udcca What does it analyze?<\/h4>\n\n\n\n<p><strong>Multi-level polarity: <\/strong>very positive \u2192 very negative (often mapped to star ratings or 0\u2013100 scores)<\/p>\n\n\n\n<h4 class=\"wp-block-heading\" id=\"best1\">\u2b50 Best for:<\/h4>\n\n\n\n<p>Surveys, NPS data, app store reviews<\/p>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"emotion-analysis\">2. Emotion analysis<\/h3>\n\n\n\n<h4 class=\"wp-block-heading\" id=\"what2\">\ud83d\udcca What does it analyze?<\/h4>\n\n\n\n<p><strong>Specific emotions: <\/strong>Goes beyond polarity and identifies joy, anger, sadness, fear, disgust, admiration, etc.<\/p>\n\n\n\n<figure data-wp-context=\"{&quot;imageId&quot;:&quot;6a5a28f5ddf6c&quot;}\" data-wp-interactive=\"core\/image\" data-wp-key=\"6a5a28f5ddf6c\" class=\"wp-block-image size-full wp-lightbox-container\"><img loading=\"lazy\" decoding=\"async\" width=\"559\" height=\"800\" data-wp-class--hide=\"state.isContentHidden\" data-wp-class--show=\"state.isContentVisible\" data-wp-init=\"callbacks.setButtonStyles\" data-wp-on--click=\"actions.showLightbox\" data-wp-on--load=\"callbacks.setButtonStyles\" data-wp-on-window--resize=\"callbacks.setButtonStyles\" src=\"https:\/\/brand24.com\/blog\/app\/uploads\/2025\/09\/sentiment-analysis-emotions-1.png\" alt=\"\" class=\"wp-image-184778\" srcset=\"https:\/\/brand24.com\/blog\/app\/uploads\/2025\/09\/sentiment-analysis-emotions-1.png 559w, https:\/\/brand24.com\/blog\/app\/uploads\/2025\/09\/sentiment-analysis-emotions-1-8x12.png 8w, https:\/\/brand24.com\/blog\/app\/uploads\/2025\/09\/sentiment-analysis-emotions-1-300x429.png 300w, https:\/\/brand24.com\/blog\/app\/uploads\/2025\/09\/sentiment-analysis-emotions-1-111x159.png 111w, https:\/\/brand24.com\/blog\/app\/uploads\/2025\/09\/sentiment-analysis-emotions-1-63x90.png 63w\" sizes=\"auto, (max-width: 559px) 100vw, 559px\" \/><button\n\t\t\tclass=\"lightbox-trigger\"\n\t\t\ttype=\"button\"\n\t\t\taria-haspopup=\"dialog\"\n\t\t\taria-label=\"Enlarge\"\n\t\t\tdata-wp-init=\"callbacks.initTriggerButton\"\n\t\t\tdata-wp-on--click=\"actions.showLightbox\"\n\t\t\tdata-wp-style--right=\"state.imageButtonRight\"\n\t\t\tdata-wp-style--top=\"state.imageButtonTop\"\n\t\t>\n\t\t\t<svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"12\" height=\"12\" fill=\"none\" viewBox=\"0 0 12 12\">\n\t\t\t\t<path fill=\"#fff\" d=\"M2 0a2 2 0 0 0-2 2v2h1.5V2a.5.5 0 0 1 .5-.5h2V0H2Zm2 10.5H2a.5.5 0 0 1-.5-.5V8H0v2a2 2 0 0 0 2 2h2v-1.5ZM8 12v-1.5h2a.5.5 0 0 0 .5-.5V8H12v2a2 2 0 0 1-2 2H8Zm2-12a2 2 0 0 1 2 2v2h-1.5V2a.5.5 0 0 0-.5-.5H8V0h2Z\" \/>\n\t\t\t<\/svg>\n\t\t<\/button><figcaption class=\"wp-element-caption\">An example of emotion analysis (Source: Brand24 tool)<\/figcaption><\/figure>\n\n\n\n<h4 class=\"wp-block-heading\" id=\"best2\">\u2b50 Best for:<\/h4>\n\n\n\n<p>Community health, campaign emotional impact, crisis detection<\/p>\n\n\n<div class=\"acf-testimonial acf-testimonial--default\">\n                    <div class=\"acf-testimonial__answer\">Emoji and emotion analysis gave me valuable insights, allowing me to read between the lines and understand how people feel about the scents, not just what they think or say.<\/div>\n        <div class=\"acf-testimonial__row\">\n                <div class=\"acf-testimonial__author-content\">\n                            <div class=\"acf-testimonial__author-name\">Anna Hynowska                            <\/div>\n                                        <div class=\"acf-testimonial__author-position\">SWPS University<\/div>\n                    <\/div>\n    <\/div>\n    <\/div>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"intent-based\">3. Intent-based analysis<\/h3>\n\n\n\n<h4 class=\"wp-block-heading\" id=\"what3\">\ud83d\udcca What does it analyze?<\/h4>\n\n\n\n<p><strong>User intention behind the message:<\/strong> complaint, praise, suggestion, purchase intent, request for help<\/p>\n\n\n\n<figure data-wp-context=\"{&quot;imageId&quot;:&quot;6a5a28f5de9c0&quot;}\" data-wp-interactive=\"core\/image\" data-wp-key=\"6a5a28f5de9c0\" class=\"wp-block-image size-large wp-lightbox-container\"><img loading=\"lazy\" decoding=\"async\" width=\"1140\" height=\"617\" data-wp-class--hide=\"state.isContentHidden\" data-wp-class--show=\"state.isContentVisible\" data-wp-init=\"callbacks.setButtonStyles\" data-wp-on--click=\"actions.showLightbox\" data-wp-on--load=\"callbacks.setButtonStyles\" data-wp-on-window--resize=\"callbacks.setButtonStyles\" src=\"https:\/\/brand24.com\/blog\/app\/uploads\/2025\/09\/sentiment-analysis-intent-1-1140x617.png\" alt=\"\" class=\"wp-image-184781\" srcset=\"https:\/\/brand24.com\/blog\/app\/uploads\/2025\/09\/sentiment-analysis-intent-1-1140x617.png 1140w, https:\/\/brand24.com\/blog\/app\/uploads\/2025\/09\/sentiment-analysis-intent-1-18x10.png 18w, https:\/\/brand24.com\/blog\/app\/uploads\/2025\/09\/sentiment-analysis-intent-1-300x162.png 300w, https:\/\/brand24.com\/blog\/app\/uploads\/2025\/09\/sentiment-analysis-intent-1-248x134.png 248w, https:\/\/brand24.com\/blog\/app\/uploads\/2025\/09\/sentiment-analysis-intent-1-90x49.png 90w, https:\/\/brand24.com\/blog\/app\/uploads\/2025\/09\/sentiment-analysis-intent-1.png 1200w\" sizes=\"auto, (max-width: 1140px) 100vw, 1140px\" \/><button\n\t\t\tclass=\"lightbox-trigger\"\n\t\t\ttype=\"button\"\n\t\t\taria-haspopup=\"dialog\"\n\t\t\taria-label=\"Enlarge\"\n\t\t\tdata-wp-init=\"callbacks.initTriggerButton\"\n\t\t\tdata-wp-on--click=\"actions.showLightbox\"\n\t\t\tdata-wp-style--right=\"state.imageButtonRight\"\n\t\t\tdata-wp-style--top=\"state.imageButtonTop\"\n\t\t>\n\t\t\t<svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"12\" height=\"12\" fill=\"none\" viewBox=\"0 0 12 12\">\n\t\t\t\t<path fill=\"#fff\" d=\"M2 0a2 2 0 0 0-2 2v2h1.5V2a.5.5 0 0 1 .5-.5h2V0H2Zm2 10.5H2a.5.5 0 0 1-.5-.5V8H0v2a2 2 0 0 0 2 2h2v-1.5ZM8 12v-1.5h2a.5.5 0 0 0 .5-.5V8H12v2a2 2 0 0 1-2 2H8Zm2-12a2 2 0 0 1 2 2v2h-1.5V2a.5.5 0 0 0-.5-.5H8V0h2Z\" \/>\n\t\t\t<\/svg>\n\t\t<\/button><figcaption class=\"wp-element-caption\">An example of intent-based, AI-powered sentiment analysis (Source: Brand24 tool)<\/figcaption><\/figure>\n\n\n\n<h4 class=\"wp-block-heading\" id=\"best3\">\u2b50 Best for:<\/h4>\n\n\n\n<p>Customer service triage, support routing, sales signals<\/p>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"aspect-based\">4. Aspect-based sentiment analysis (ABSA)<\/h3>\n\n\n\n<h4 class=\"wp-block-heading\" id=\"what4\">\ud83d\udcca What does it analyze?<\/h4>\n\n\n\n<p><strong>Sentiment per feature or topic<\/strong>, for example: <em>&#8220;app: positive, notifications: negative&#8221;<\/em><\/p>\n\n\n\n<figure data-wp-context=\"{&quot;imageId&quot;:&quot;6a5a28f5df058&quot;}\" data-wp-interactive=\"core\/image\" data-wp-key=\"6a5a28f5df058\" class=\"wp-block-image size-large wp-lightbox-container\"><img loading=\"lazy\" decoding=\"async\" width=\"1140\" height=\"616\" data-wp-class--hide=\"state.isContentHidden\" data-wp-class--show=\"state.isContentVisible\" data-wp-init=\"callbacks.setButtonStyles\" data-wp-on--click=\"actions.showLightbox\" data-wp-on--load=\"callbacks.setButtonStyles\" data-wp-on-window--resize=\"callbacks.setButtonStyles\" src=\"https:\/\/brand24.com\/blog\/app\/uploads\/2025\/09\/sentiment-analysis-topics-1-1140x616.png\" alt=\"\" class=\"wp-image-184779\" srcset=\"https:\/\/brand24.com\/blog\/app\/uploads\/2025\/09\/sentiment-analysis-topics-1-1140x616.png 1140w, https:\/\/brand24.com\/blog\/app\/uploads\/2025\/09\/sentiment-analysis-topics-1-18x10.png 18w, https:\/\/brand24.com\/blog\/app\/uploads\/2025\/09\/sentiment-analysis-topics-1-300x162.png 300w, https:\/\/brand24.com\/blog\/app\/uploads\/2025\/09\/sentiment-analysis-topics-1-248x134.png 248w, https:\/\/brand24.com\/blog\/app\/uploads\/2025\/09\/sentiment-analysis-topics-1-90x49.png 90w, https:\/\/brand24.com\/blog\/app\/uploads\/2025\/09\/sentiment-analysis-topics-1.png 1199w\" sizes=\"auto, (max-width: 1140px) 100vw, 1140px\" \/><button\n\t\t\tclass=\"lightbox-trigger\"\n\t\t\ttype=\"button\"\n\t\t\taria-haspopup=\"dialog\"\n\t\t\taria-label=\"Enlarge\"\n\t\t\tdata-wp-init=\"callbacks.initTriggerButton\"\n\t\t\tdata-wp-on--click=\"actions.showLightbox\"\n\t\t\tdata-wp-style--right=\"state.imageButtonRight\"\n\t\t\tdata-wp-style--top=\"state.imageButtonTop\"\n\t\t>\n\t\t\t<svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"12\" height=\"12\" fill=\"none\" viewBox=\"0 0 12 12\">\n\t\t\t\t<path fill=\"#fff\" d=\"M2 0a2 2 0 0 0-2 2v2h1.5V2a.5.5 0 0 1 .5-.5h2V0H2Zm2 10.5H2a.5.5 0 0 1-.5-.5V8H0v2a2 2 0 0 0 2 2h2v-1.5ZM8 12v-1.5h2a.5.5 0 0 0 .5-.5V8H12v2a2 2 0 0 1-2 2H8Zm2-12a2 2 0 0 1 2 2v2h-1.5V2a.5.5 0 0 0-.5-.5H8V0h2Z\" \/>\n\t\t\t<\/svg>\n\t\t<\/button><figcaption class=\"wp-element-caption\">An example of aspect-based sentiment analysis that evaluates sentiment around specific topics in discussions about IKEA (Source: Brand24 tool)<\/figcaption><\/figure>\n\n\n\n<h4 class=\"wp-block-heading\" id=\"best4\">\u2b50 Best for:<\/h4>\n\n\n\n<p>Product development, competitive feature analysis, UX research<\/p>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"algorithm-types\">How does sentiment analysis work? The three algorithm types<\/h3>\n\n\n\n<p>Sentiment analysis tools use various types of algorithms. Understanding which approach a tool uses tells you a lot about where it will perform well and where it will struggle.<\/p>\n\n\n\n<h4 class=\"wp-block-heading\" id=\"machine-learning\">1. Machine learning (automatic)<\/h4>\n\n\n\n<h5 class=\"wp-block-heading\" id=\"how1\">\u2699\ufe0f How does it work?<\/h5>\n\n\n\n<p>It\u2019s trained on large, labeled datasets, learns patterns from them, and then uses those patterns to make sense of new text<\/p>\n\n\n\n<h5 class=\"wp-block-heading\" id=\"strength1\">\ud83d\udcaa Strengths:<\/h5>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Can handle huge volumes of data<\/li>\n\n\n\n<li>Keeps getting better as it sees more and more data<\/li>\n\n\n\n<li>No manual rules to build or maintain<\/li>\n<\/ul>\n\n\n\n<h5 class=\"wp-block-heading\" id=\"limitation1\">\u26a0\ufe0f Limitations:<\/h5>\n\n\n\n<ul class=\"wp-block-list\">\n<li>It\u2019s a bit of a \u201cblack box\u201d, so it can\u2019t always explain why it made a decision<\/li>\n\n\n\n<li>Accuracy depends heavily on the quality of the training data<\/li>\n<\/ul>\n\n\n\n<h4 class=\"wp-block-heading\" id=\"rule-based\">2. Rule-based (lexicon)<\/h4>\n\n\n\n<h5 class=\"wp-block-heading\">\u2699\ufe0f How does it work?<\/h5>\n\n\n\n<p>It depends on predefined word lists where each word has a positive or negative score, using straightforward, transparent rules.<\/p>\n\n\n\n<h5 class=\"wp-block-heading\">\ud83d\udcaa Strengths:<\/h5>\n\n\n\n<p>It\u2019s fast, easy to understand, and simple to use<\/p>\n\n\n\n<h5 class=\"wp-block-heading\">\u26a0\ufe0f Limitations:<\/h5>\n\n\n\n<p>It can struggle with negation, sarcasm, and more informal language<\/p>\n\n\n\n<h4 class=\"wp-block-heading\" id=\"hybrid\">3. Hybrid<\/h4>\n\n\n\n<h5 class=\"wp-block-heading\">\u2699\ufe0f How does it work?<\/h5>\n\n\n\n<p>It blends machine learning accuracy with the consistency of rule-based logic<\/p>\n\n\n\n<h5 class=\"wp-block-heading\">\ud83d\udcaa Strengths:<\/h5>\n\n\n\n<p>Very reliable overall: it picks up what you\u2019d miss using only ML or only rules<\/p>\n\n\n\n<h5 class=\"wp-block-heading\">\u26a0\ufe0f Limitations:<\/h5>\n\n\n\n<p>It\u2019s more complicated to build and maintain<\/p>\n\n\n\n<p class=\"has-background\" style=\"background-color:#e8f4ee\">\ud83d\udca1 Most enterprise-grade tools, including Brand24, use <strong>a hybrid approach<\/strong>, which is why they outperform single-method tools on real-world social media text.<\/p>\n\n\n<style>.acf-simple-cta{border-radius:20px;background-color:#fff;max-width:640px;margin:auto;margin-bottom:30px;padding:30px 15px}@media(min-width: 768px){.acf-simple-cta{padding:48px 62px 46px 62px}}.acf-simple-cta__title{font-size:22px !important;font-weight:600;line-height:23px !important;color:#000;text-align:center;margin-top:10px}@media(min-width: 576px){.acf-simple-cta__title{max-width:280px;text-align:left;margin-top:0}}.acf-simple-cta__title span{color:#00ef88}.acf-simple-cta__row{text-align:center}@media(min-width: 768px){.acf-simple-cta__row{display:flex;align-items:center;justify-content:space-between;gap:10px;text-align:left}}.acf-simple-cta__content{margin-bottom:20px;text-align:center}@media(min-width: 576px){.acf-simple-cta__content{display:flex;justify-content:center;align-items:center;gap:10px;width:100%;max-width:100%}}@media(min-width: 768px){.acf-simple-cta__content{align-items:center;justify-content:space-between;margin-bottom:0;max-width:66%}}.acf-simple-cta__btn{flex-shrink:0;border-radius:30px;padding:11px 21px;font-size:14px;line-height:18px;font-weight:500 !important;color:#000 !important;letter-spacing:-0.14px;background-color:#00ef88;border:none;transition:background-color .3s ease,opacity .3s ease;display:inline-block}.acf-simple-cta__btn:hover{background-color:#4bffae;text-decoration:none;opacity:.9}.acf-simple-cta__btn:focus-visible{outline:2px solid #00ef88}.acf-simple-cta--primary{background-color:#00ef88}.acf-simple-cta--primary .acf-simple-cta__title{color:#fff}.acf-simple-cta--primary .acf-simple-cta__title span{color:#000}.acf-simple-cta--primary .acf-simple-cta__btn{background-color:#000;color:#fff !important;transition:background-color .3s ease-in-out}.acf-simple-cta--primary .acf-simple-cta__btn:hover{background-color:#171717}.acf-simple-cta--violet{background-color:#000}.acf-simple-cta--violet .acf-simple-cta__title{color:#fff}.acf-simple-cta--violet .acf-simple-cta__title span{color:#bf00ff}.acf-simple-cta--violet .acf-simple-cta__btn{background-color:#bf00ff;color:#000 !important;transition:background-color .3s ease-in-out}.acf-simple-cta--violet .acf-simple-cta__btn:hover{background-color:#bf00ff}.acf-simple-cta--small{padding:20px 15px}@media(min-width: 768px){.acf-simple-cta--small{padding:33px 45px 31px 56px}}.acf-simple-cta--no-icon .acf-simple-cta__content{max-width:100%;width:auto}.acf-simple-cta--no-icon .acf-simple-cta__title{max-width:100%}@media(min-width: 768px){.acf-simple-cta--no-icon.acf-simple-cta--small .acf-simple-cta__content{max-width:55%}}<\/style>\n<div class=\"acf-simple-cta acf-simple-cta--default acf-simple-cta--no-icon acf-simple-cta--small\">\n    <div class=\"acf-simple-cta__wrapper\">\n        <div class=\"acf-simple-cta__row\">\n            <div class=\"acf-simple-cta__content\">\n                                                    <div class=\"acf-simple-cta__title\">Start Sentiment Analysis Now!<\/div>\n                            <\/div>\n                            <a href=\"https:\/\/app.brand24.com\/user\/register-account\/?custom_form=118\" class=\"acf-simple-cta__btn\" target=\"\">Start Trial!<\/a>\n                    <\/div>\n    <\/div>\n<\/div>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"original-research\">What do people say online about sentiment analysis? [Original research] <\/h2>\n\n\n\n<p>To understand how sentiment analysis is discussed online in 2026, I used Brand24&#8217;s <a href=\"https:\/\/brand24.com\/brand-assistant\/\" target=\"_blank\" rel=\"noopener\" title=\"\">AI Brand Assistant<\/a> to analyze online mentions of <em>&#8220;sentiment analysis&#8221;<\/em> across social and non-social media.<\/p>\n\n\n\n<p>Let&#8217;s see what marketers find useful in sentiment analysis, what frustrates them, and what they&#8217;re using it for in 2026.<\/p>\n\n\n\n<p><strong>Here&#8217;s a snapshot of what I found before going deeper:<\/strong><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Most of the sentiment analysis discussion right now focuses on <strong>AI and practical business use cases<\/strong><\/li>\n\n\n\n<li><strong>Finance and trading communities<\/strong> are leading the conversation and driving the most reach.<\/li>\n\n\n\n<li><strong>The biggest pain point is interpretation:<\/strong> models still often miss sarcasm, cultural slang, and more nuanced language.<\/li>\n\n\n\n<li><strong>Brand24<\/strong> stands out as the only top-mentioned tool that includes <strong>a dedicated AI Visibility tracking feature<\/strong><\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"how-big\">How big is the conversation?<\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Brand24 tracked <strong>12,894 mentions<\/strong> of sentiment analysis between June 9 and July 9, 2026, generating a combined reach of <strong>23.7M<\/strong>.<\/li>\n\n\n\n<li>Of those mentions, <strong>4,469 (34.7%)<\/strong> had a direct marketing context<\/li>\n<\/ul>\n\n\n\n<p><strong>Sentiment distribution across the full conversation:<\/strong><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Positive<\/strong>: 5%<\/li>\n\n\n\n<li><strong>Negative<\/strong>: 1% <\/li>\n\n\n\n<li><strong>Neutral<\/strong>: 94% <\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"key-topics\">What are key topics of discussion around sentiment analysis?<\/h3>\n\n\n\n<p>When Brand24&#8217;s AI grouped the online conversation into clusters, I found <strong>7 distinct topics<\/strong>. <\/p>\n\n\n\n<p>Here&#8217;s a summary:<\/p>\n\n\n\n<figure class=\"wp-block-table is-style-comparison-table\"><table><thead><tr><th>Topic<\/th><th>Mentions<\/th><th>Reach<\/th><th>Share of voice<\/th><th>Sentiment analysis discussed in<\/th><\/tr><\/thead><tbody><tr><td><strong>Sentiment Analysis Solutions<\/strong><\/td><td><strong>2,683<\/strong><\/td><td>2.3M<\/td><td>19.7%<\/td><td>AI-powered tool roundups, feature comparisons, how-to guides<\/td><\/tr><tr><td><strong>Financial Market Intelligence<\/strong><\/td><td>1,509<\/td><td>3.1M<\/td><td>25.8%<\/td><td>Stocks, crypto, forex, treating sentiment as a tradeable signal<\/td><\/tr><tr><td><strong>AI Business Solutions<\/strong><\/td><td>1,440<\/td><td><strong>4.4M<\/strong><\/td><td><strong>36.9%<\/strong><\/td><td>A core component of enterprise AI embedded in chatbots, pipelines, executive dashboards<\/td><\/tr><tr><td><strong>Social Media Analytics<\/strong><\/td><td>589<\/td><td>895K<\/td><td>7.6%<\/td><td>Brand monitoring, reputation management, audience tracking<\/td><\/tr><tr><td><strong>Natural Language Processing<\/strong><\/td><td>189<\/td><td>362K<\/td><td>3.1%<\/td><td>Technical discussions: model architectures, developer toolkits<\/td><\/tr><tr><td><strong>AI Search Brand Visibility<\/strong><\/td><td>203<\/td><td>287K<\/td><td>2.4%<\/td><td>Using it to score how AI chatbots talk about a brand<\/td><\/tr><tr><td><strong>Brand Metrics Measurement<\/strong><\/td><td>207<\/td><td>53K<\/td><td>0.5%<\/td><td>One KPI among many: guides, dashboards, benchmarking frameworks<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"marketing-context\">What are the key topics in the marketing context specifically?<\/h3>\n\n\n\n<p>When I filtered to mentions with a <strong>marketing angle specifically<\/strong>, 4 different use cases showed up from the 4,469 marketing-context mentions:<\/p>\n\n\n\n<p><strong>A short summary of the conversation:<\/strong><\/p>\n\n\n\n<figure class=\"wp-block-table is-style-comparison-table\"><table><thead><tr><th>Theme<\/th><th>What people discuss<\/th><\/tr><\/thead><tbody><tr><td><strong>Brand Monitoring &amp; Brand Perception<\/strong><\/td><td>SA as the mechanism behind <strong>understanding how customers talk about a brand online<\/strong>, used in SEO to replace traditional keyword ranking reports<\/td><\/tr><tr><td><strong>Customer Experience &amp; Review Analysis<\/strong><\/td><td>SA as a <strong>standard KPI tool <\/strong>alongside reach, impressions, and engagement, tracked in tools like Hootsuite and Google Analytics<\/td><\/tr><tr><td><strong>Reputation Management &amp; PR \/ Crisis Communication<\/strong><\/td><td>SA alongside Share of Voice as <em>&#8220;essential components of robust media intelligence&#8221;<\/em> <strong>for proactive crisis mitigation<\/strong><\/td><\/tr><tr><td><strong>AI-Powered Media Intelligence &amp; Competitive Benchmarking<\/strong><\/td><td>SA in AI-driven platforms, used to benchmark <strong>how positively AI chatbots mention brands<\/strong> compared to your competitors<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n<p><strong>Top hashtags in the marketing conversation:<\/strong><\/p>\n\n\n\n<figure class=\"wp-block-table is-style-comparison-table\"><table><thead><tr><th>Hashtag<\/th><th>Mentions<\/th><th>Context<\/th><\/tr><\/thead><tbody><tr><td><strong>#ai<\/strong><\/td><td>10<\/td><td>Top overall<\/td><\/tr><tr><td><strong>#sentimentanalysis<\/strong><\/td><td>8<\/td><td>Category-specific<\/td><\/tr><tr><td><strong>#digitalmarketing<\/strong><\/td><td>6<\/td><td>Most marketing-specific<\/td><\/tr><tr><td><strong>#geo<\/strong><\/td><td>5<\/td><td>Generative Engine Optimization: an emerging trend<\/td><\/tr><tr><td><strong>#digitaltransformation<\/strong><\/td><td>4<\/td><td>Business and enterprise angle<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n<p><strong>Emotions in the marketing-context discussions:<\/strong><\/p>\n\n\n\n<figure class=\"wp-block-table is-style-comparison-table\"><table><thead><tr><th>Emotion<\/th><th>Share<\/th><th>vs. General sentiment analysis discussions<\/th><\/tr><\/thead><tbody><tr><td><strong>Trust<\/strong><\/td><td>35.9%<\/td><td>-2.1pp<\/td><\/tr><tr><td><strong>Joy<\/strong><\/td><td>17.2%<\/td><td>-1.8pp<\/td><\/tr><tr><td><strong>Anticipation<\/strong><\/td><td>17.0%<\/td><td>-1.0pp<\/td><\/tr><tr><td><strong>Distrust<\/strong><\/td><td>11.2%<\/td><td>+2.1pp above baseline<\/td><\/tr><tr><td><strong>Anger<\/strong><\/td><td>7.1%<\/td><td>+2.3pp above baseline<\/td><\/tr><tr><td><strong>Fear<\/strong><\/td><td>5.8%<\/td><td>+2.6pp \u2014 nearly doubled vs. baseline<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"top-challenges\">What are top challenges in sentiment analysis?<\/h3>\n\n\n\n<p>When I filtered mentions for challenge-related keywords, eight recurring pain points emerged:<\/p>\n\n\n\n<figure class=\"wp-block-table is-style-comparison-table\"><table><thead><tr><th>Challenge<\/th><th>What it means<\/th><th>Example from the data<\/th><\/tr><\/thead><tbody><tr><td><strong>Accuracy limitations<\/strong><\/td><td>Even production-ready models still have about an 8% error rate, and there\u2019s no way to know ahead of time which 8% will be wrong<\/td><td><em>&#8220;A sentiment analysis model considered production-ready at 92% accuracy still means 8% of outputs are wrong and you can&#8217;t predict which 8%.&#8221;<\/em><\/td><\/tr><tr><td><strong>Context &amp; nuance blindness<\/strong><\/td><td>Models miss sarcasm, irony, and complex narrative structure<\/td><td><em>&#8220;Sentiment analysis is fundamentally flawed when applied to narratives. The lack of coherence is precisely the point.&#8221;<\/em><\/td><\/tr><tr><td><strong>Cultural &amp; linguistic bias<\/strong><\/td><td>Models trained mainly on English underperform on AAVE, Arabic, Filipino English, or Thai<\/td><td><em>&#8220;Leading sentiment models misclassify nuanced emotional content up to 35% of the time, with Filipino English among the highest error rates.&#8221;<\/em><\/td><\/tr><tr><td><strong>Platform coverage gaps<\/strong><\/td><td>Tools optimized for X\/Twitter provide shallow coverage on Discord, Bluesky, or other emerging platforms<\/td><td><em>&#8220;Twitter sentiment models miss too much. Discord analytics give you the surface-level version of what&#8217;s going on.&#8221;<\/em><\/td><\/tr><tr><td><strong>Generic model failures<\/strong><\/td><td>One-size-fits-all models fail in niche markets, industry jargon, and regional cultural contexts<\/td><td><em>&#8220;Review sentiment analysis is often misinterpreted by automation because it fails to distinguish between generic praise and location-specific justifications.&#8221;<\/em><\/td><\/tr><tr><td><strong>Mandatory manual review<\/strong><\/td><td>Marketers advise against full automation, even in 2026<\/td><td><em>&#8220;Set the sentiment analysis to &#8216;automatic&#8217; initially, but always manually review the results for accuracy.&#8221;<\/em><\/td><\/tr><tr><td><strong>Explainability<\/strong><\/td><td>As AI models get more accurate, they often become harder to understand, which can be a real issue in regulated industries<\/td><td>Academic papers point to hybrid CNN\u2013LSTM + XAI frameworks as the research response to this<\/td><\/tr><tr><td><strong>Benchmarking &amp; data quality<\/strong><\/td><td>Proprietary benchmarks aren\u2019t very transparent, and negative data poisoning is becoming a serious threat<\/td><td><em>&#8220;There&#8217;s a billion language models on HuggingFace that could do this locally and let you quantify how inaccurate it is with benchmarks.&#8221;<\/em><\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"sentiment-tools\">Which sentiment analysis tools are most frequently mentioned?<\/h3>\n\n\n\n<p>Discussions referencing specific tools generated <strong>1,584 mentions and 2.6M reach<\/strong>. Here&#8217;s how the most-cited commercial platforms are described online:<\/p>\n\n\n\n<figure class=\"wp-block-table is-style-comparison-table has-row-numbers\"><table><thead><tr><th>Tool<\/th><th>How it&#8217;s described in people&#8217;s discussions<\/th><\/tr><\/thead><tbody><tr><td><strong>Brandwatch<\/strong><\/td><td>Go-to enterprise platform<\/td><\/tr><tr><td><strong>Sprout Social<\/strong><\/td><td>Praised for real-time sentiment analysis and comprehensive reporting<\/td><\/tr><tr><td><strong>Meltwater<\/strong><\/td><td>Dominant in PR and earned media contexts<\/td><\/tr><tr><td><strong>Sprinklr<\/strong><\/td><td>Cited for enterprise social listening integration<\/td><\/tr><tr><td><strong>Talkwalker<\/strong><\/td><td>Regularly paired with Brandwatch in trend-spotting recommendations<\/td><\/tr><tr><td><strong>Brand24<\/strong><\/td><td>Noted for AI-powered monitoring use cases and emotion analysis<\/td><\/tr><tr><td><strong>Hootsuite<\/strong><\/td><td>AI sorts mentions by sentiment<\/td><\/tr><tr><td><strong>Semrush<\/strong><\/td><td>Referenced for brand monitoring module with built-in sentiment alerts<\/td><\/tr><tr><td><strong>MeaningCloud<\/strong><\/td><td>Used by practitioners for topic extraction in custom Python pipelines<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"industries\">Which industries most actively discuss sentiment analysis?<\/h3>\n\n\n\n<p>A quick summary:<\/p>\n\n\n\n<figure class=\"wp-block-table is-style-comparison-table\"><table><thead><tr><th>Industry<\/th><th>Mentions<\/th><th>Key use case<\/th><\/tr><\/thead><tbody><tr><td><strong>Marketing &amp; PR<\/strong><\/td><td>2,000<\/td><td>Campaign monitoring, reputation management, and crisis detection; SA integrated into editorial calendars and PR response protocols<\/td><\/tr><tr><td><strong>Finance \/ Trading<\/strong><\/td><td>1,510<\/td><td>Real-time market mood signals; crypto traders apply SA to gauge market sentiment via fear\/greed indices and social chatter<\/td><\/tr><tr><td><strong>E-commerce &amp; Retail<\/strong><\/td><td>~800<\/td><td>Product review mining on Amazon and review platforms; complaint clustering and competitor benchmarking<\/td><\/tr><tr><td><strong>HR &amp; Employee Experience<\/strong><\/td><td>~400<\/td><td>Continuous listening platforms; HR teams shifting from annual surveys to always-on sentiment monitoring of Slack and collaboration tools<\/td><\/tr><tr><td><strong>Customer Service<\/strong><\/td><td>~300<\/td><td>Real-time voice analytics; call centers use SA to score agent empathy, detect customer frustration, and route escalations<\/td><\/tr><tr><td><strong>Tech \/ Developer<\/strong><\/td><td>~190<\/td><td>Model building, benchmarking, open-source framework discussions<\/td><\/tr><tr><td><strong>Academic Research<\/strong><\/td><td>~65<\/td><td>ABSA, multilingual models, multimodal SA across linguistics and computer science<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n<div class=\"acf-simple-cta acf-simple-cta--primary acf-simple-cta--no-icon acf-simple-cta--small\">\n    <div class=\"acf-simple-cta__wrapper\">\n        <div class=\"acf-simple-cta__row\">\n            <div class=\"acf-simple-cta__content\">\n                                                    <div class=\"acf-simple-cta__title\">Start Sentiment Analysis Now!<\/div>\n                            <\/div>\n                            <a href=\"https:\/\/app.brand24.com\/user\/register-account\/?custom_form=118\" class=\"acf-simple-cta__btn\" target=\"\">Start Trial!<\/a>\n                    <\/div>\n    <\/div>\n<\/div>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"sentiment-inteligence-loop\">How to do sentiment analysis effectively? The Brand24 Sentiment Intelligence Loop<\/h2>\n\n\n\n<p>From what I\u2019ve seen looking at sentiment analysis data across different industries, the brands that get real, measurable results treat it as an ongoing feedback loop.<\/p>\n\n\n\n<p>Each step builds on the last, and every cycle makes the insights clearer and more useful.<\/p>\n\n\n\n<p>This framework is called the <strong>Brand24 Sentiment Intelligence Loop<\/strong>:<\/p>\n\n\n<div class=\"acf-numeric-list\">\n    <ul class=\"acf-numeric-list__list\">\n                    <li class=\"acf-numeric-list__item\">\n                <span class=\"acf-numeric-list__number\">1<\/span>\n                <span class=\"acf-numeric-list__text\">Define your signal<\/span>\n            <\/li>\n                    <li class=\"acf-numeric-list__item\">\n                <span class=\"acf-numeric-list__number\">2<\/span>\n                <span class=\"acf-numeric-list__text\">Build multi-source listening<\/span>\n            <\/li>\n                    <li class=\"acf-numeric-list__item\">\n                <span class=\"acf-numeric-list__number\">3<\/span>\n                <span class=\"acf-numeric-list__text\">Decode sentiment in layers<\/span>\n            <\/li>\n                    <li class=\"acf-numeric-list__item\">\n                <span class=\"acf-numeric-list__number\">4<\/span>\n                <span class=\"acf-numeric-list__text\">Act on the signal<\/span>\n            <\/li>\n                    <li class=\"acf-numeric-list__item\">\n                <span class=\"acf-numeric-list__number\">5<\/span>\n                <span class=\"acf-numeric-list__text\">Benchmark your own sentiment history<\/span>\n            <\/li>\n            <\/ul>\n<\/div>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"step1\">Step 1: Define your signal \u2014 what sentiment shift would change your strategy?<\/h3>\n\n\n\n<p>I recommend starting with a question: <\/p>\n\n\n\n<p class=\"has-background\" style=\"background-color:#e8f4ee\"><strong><em>What would you do differently if positive sentiment dropped by 10%?<\/em> <\/strong><\/p>\n\n\n\n<p>Before setting up any sentiment analysis project, define:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>What keywords you&#8217;re tracking: <\/strong>brand name, product names, spokesperson names, campaign hashtags, and common misspellings<\/li>\n\n\n\n<li><strong>What\u2019s the trigger point for taking action: <\/strong>a 10% drop in positive sentiment? A spike in anger-classified mentions? Negative sentiment reaching 20%?<\/li>\n\n\n\n<li><strong>What is your reference level: <\/strong>you can&#8217;t spot anomalies without a reference point<\/li>\n<\/ul>\n\n\n\n<p class=\"has-background\" style=\"background-color:#e8f4ee\">\ud83d\udca1 <strong>I recommend running four social media monitoring projects in parallel: <\/strong>brand monitoring, active campaign tracking, competitor monitoring, and an industry keyword project. Each gives you a different layer of the sentiment picture.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"step2\">Step 2: Build multi-source social listening <\/h3>\n\n\n\n<p>Manual monitoring covers maybe 5% of what&#8217;s actually being said about you. Real sentiment analysis and <a href=\"https:\/\/brand24.com\/blog\/what-is-social-listening\/\" target=\"_blank\" rel=\"noopener\" title=\"\">social listening<\/a> require automated collection across:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Social platforms:<\/strong> X\/Twitter, Instagram, Facebook, TikTok, LinkedIn, YouTube<\/li>\n\n\n\n<li><strong>Forums and communities: <\/strong>Reddit, Quora, Discord<\/li>\n\n\n\n<li><strong>Review platforms:<\/strong> Google Reviews, Trustpilot, G2, Capterra, App Store, Play Store<\/li>\n\n\n\n<li><strong>Video platforms: <\/strong>YouTube (including YouTube transcript monitoring), Twitch<\/li>\n\n\n\n<li>News sites, blogs, and podcasts<\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"step3\">Step 3: Decode sentiment in layers<\/h3>\n\n\n\n<p><strong>Sentiment<\/strong> <strong>polarity<\/strong>: tells you the direction. <\/p>\n\n\n\n<p><strong>Emotion<\/strong> <strong>analysis: <\/strong>tells you the intensity and type of feeling. <\/p>\n\n\n\n<p><a href=\"https:\/\/brand24.com\/blog\/topic-analysis\/\" title=\"Get Better Insights with the New Topic Analysis!\"><strong>Topic<\/strong> <strong>Analysis<\/strong><\/a>: tells you <em>why<\/em> people love or hate a brand, product, or idea.<\/p>\n\n\n\n<p>I recommend looking at all three together, in that order:<\/p>\n\n\n\n<figure class=\"wp-block-table is-style-comparison-table\"><table><thead><tr><th>Layer<\/th><th>What to look at<\/th><th>Examples of what it tells you<\/th><\/tr><\/thead><tbody><tr><td><strong>Sentiment polarity<\/strong><\/td><td>What is the positive\/negative ratio trend?<\/td><td>A drop from 75% to 62% positive over two weeks is more actionable than &#8220;62% positive today&#8221;<\/td><\/tr><tr><td><strong>Emotion distribution<\/strong><\/td><td>Which emotions spike specifically?<\/td><td>When anger starts rising, even though overall negative sentiment is still low, it\u2019s a sign something\u2019s happening before it shows up in the overall data<\/td><\/tr><tr><td><strong>Topic clusters<\/strong><\/td><td>Which specific subject is driving the sentiment change?<\/td><td>Separates topics, e.g. a product quality complaint from a pricing reaction from a competitor campaign<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n<div class=\"acf-testimonial acf-testimonial--default\">\n                    <div class=\"acf-testimonial__answer\">Because numbers alone don&#8217;t tell the full story. You can track reach, clicks, or mentions \u2014 but without understanding the emotional tone behind them, you&#8217;re missing the context that really matters.\r\n<\/div>\n        <div class=\"acf-testimonial__row\">\n                <div class=\"acf-testimonial__author-content\">\n                            <div class=\"acf-testimonial__author-name\">Jorge Hoth                            <\/div>\n                                        <div class=\"acf-testimonial__author-position\">Fractional CMO &#038; Advisor<\/div>\n                    <\/div>\n    <\/div>\n    <\/div>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"step4\">Step 4: Act on the sentiment signals<\/h3>\n\n\n\n<p>Sentiment share is just another stat in your <a href=\"https:\/\/brand24.com\/blog\/social-listening-tools\/\" target=\"_blank\" rel=\"noopener\" title=\"\">social listening tool<\/a> unless you do something with it!<\/p>\n\n\n\n<p class=\"has-background\" style=\"background-color:#e8f4ee\">\ud83d\udca1 <a href=\"https:\/\/www.zendesk.com\/blog\/customer-service\/satisfaction\/customer-service-statistics\/\" target=\"_blank\" rel=\"noopener\" title=\"\">Zendesk 2026 research <\/a>shows that 85% of CX leaders say customers will drop brands over unresolved issues, even on first contact.<\/p>\n\n\n\n<p>There are three types of action that come from sentiment insights:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>React to negative mentions fast: <\/strong>Speed matters more than perfection in the first response.<\/li>\n\n\n\n<li><strong>Fix the root cause: <\/strong>If negative mentions keep popping up around the same topic, make sure the right team knows so they can fix it<\/li>\n\n\n\n<li><strong>Amplify positive advocates: <\/strong>Influencer Analysis feature surfaces the high-reach authors generating the most positive mentions &#8211; reach out to them!<\/li>\n<\/ul>\n\n\n<div class=\"acf-testimonial acf-testimonial--default\">\n                    <div class=\"acf-testimonial__answer\">Look at sentiment, reviews, mentions, and the tone of what&#8217;s being said. I pay attention to patterns in feedback and how people respond over time. These signals help you understand what&#8217;s working \u2014 and what needs to change!\r\n\r\n<\/div>\n        <div class=\"acf-testimonial__row\">\n                    <div class=\"acf-testimonial__author-image\">\n                <img decoding=\"async\" width=\"250\" height=\"250\" src=\"https:\/\/brand24.com\/blog\/app\/uploads\/2025\/05\/Phil-Pallen-2-min-1-250x250.jpg\" class=\"attachment-thumbnail size-thumbnail\" alt=\"Phil-Pallen\" loading=\"lazy\" srcset=\"https:\/\/brand24.com\/blog\/app\/uploads\/2025\/05\/Phil-Pallen-2-min-1-250x250.jpg 250w, https:\/\/brand24.com\/blog\/app\/uploads\/2025\/05\/Phil-Pallen-2-min-1-60x60.jpg 60w, https:\/\/brand24.com\/blog\/app\/uploads\/2025\/05\/Phil-Pallen-2-min-1-64x64.jpg 64w, https:\/\/brand24.com\/blog\/app\/uploads\/2025\/05\/Phil-Pallen-2-min-1-314x314.jpg 314w, https:\/\/brand24.com\/blog\/app\/uploads\/2025\/05\/Phil-Pallen-2-min-1-48x48.jpg 48w, https:\/\/brand24.com\/blog\/app\/uploads\/2025\/05\/Phil-Pallen-2-min-1-42x42.jpg 42w, https:\/\/brand24.com\/blog\/app\/uploads\/2025\/05\/Phil-Pallen-2-min-1-80x80.jpg 80w\" sizes=\"auto, (max-width: 250px) 100vw, 250px\" \/>            <\/div>\n                <div class=\"acf-testimonial__author-content\">\n                            <div class=\"acf-testimonial__author-name\">Phil Pallen                            <\/div>\n                                        <div class=\"acf-testimonial__author-position\">Brand Strategist<\/div>\n                    <\/div>\n    <\/div>\n    <\/div>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"step5\">Step 5: Benchmark your own sentiment history<\/h3>\n\n\n\n<p>Sentiment is only meaningful in comparison: a trend tells you everything!<\/p>\n\n\n\n<p>The metrics I\u2019d keep an eye on with a regular reporting schedule:<\/p>\n\n\n\n<p><strong>1. Sentiment ratio trend<\/strong><\/p>\n\n\n\n<p>Week-over-week and month-over-month: is the direction improving or declining?<\/p>\n\n\n\n<figure data-wp-context=\"{&quot;imageId&quot;:&quot;6a5a28f5e3965&quot;}\" data-wp-interactive=\"core\/image\" data-wp-key=\"6a5a28f5e3965\" class=\"wp-block-image size-large wp-lightbox-container\"><img loading=\"lazy\" decoding=\"async\" width=\"1140\" height=\"998\" data-wp-class--hide=\"state.isContentHidden\" data-wp-class--show=\"state.isContentVisible\" data-wp-init=\"callbacks.setButtonStyles\" data-wp-on--click=\"actions.showLightbox\" data-wp-on--load=\"callbacks.setButtonStyles\" data-wp-on-window--resize=\"callbacks.setButtonStyles\" src=\"https:\/\/brand24.com\/blog\/app\/uploads\/2025\/09\/sentiment-analysis-comparison-sentiment-1-1140x998.png\" alt=\"\" class=\"wp-image-184784\" srcset=\"https:\/\/brand24.com\/blog\/app\/uploads\/2025\/09\/sentiment-analysis-comparison-sentiment-1-1140x998.png 1140w, https:\/\/brand24.com\/blog\/app\/uploads\/2025\/09\/sentiment-analysis-comparison-sentiment-1-14x12.png 14w, https:\/\/brand24.com\/blog\/app\/uploads\/2025\/09\/sentiment-analysis-comparison-sentiment-1-300x263.png 300w, https:\/\/brand24.com\/blog\/app\/uploads\/2025\/09\/sentiment-analysis-comparison-sentiment-1-182x159.png 182w, https:\/\/brand24.com\/blog\/app\/uploads\/2025\/09\/sentiment-analysis-comparison-sentiment-1-90x79.png 90w, https:\/\/brand24.com\/blog\/app\/uploads\/2025\/09\/sentiment-analysis-comparison-sentiment-1.png 1200w\" sizes=\"auto, (max-width: 1140px) 100vw, 1140px\" \/><button\n\t\t\tclass=\"lightbox-trigger\"\n\t\t\ttype=\"button\"\n\t\t\taria-haspopup=\"dialog\"\n\t\t\taria-label=\"Enlarge\"\n\t\t\tdata-wp-init=\"callbacks.initTriggerButton\"\n\t\t\tdata-wp-on--click=\"actions.showLightbox\"\n\t\t\tdata-wp-style--right=\"state.imageButtonRight\"\n\t\t\tdata-wp-style--top=\"state.imageButtonTop\"\n\t\t>\n\t\t\t<svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"12\" height=\"12\" fill=\"none\" viewBox=\"0 0 12 12\">\n\t\t\t\t<path fill=\"#fff\" d=\"M2 0a2 2 0 0 0-2 2v2h1.5V2a.5.5 0 0 1 .5-.5h2V0H2Zm2 10.5H2a.5.5 0 0 1-.5-.5V8H0v2a2 2 0 0 0 2 2h2v-1.5ZM8 12v-1.5h2a.5.5 0 0 0 .5-.5V8H12v2a2 2 0 0 1-2 2H8Zm2-12a2 2 0 0 1 2 2v2h-1.5V2a.5.5 0 0 0-.5-.5H8V0h2Z\" \/>\n\t\t\t<\/svg>\n\t\t<\/button><figcaption class=\"wp-element-caption\">An example of sentiment ratio trend comparison charts (Source: Brand24 tool)<\/figcaption><\/figure>\n\n\n\n<ol class=\"wp-block-list\"><\/ol>\n\n\n\n<p><strong>2. Sentiment by platform<\/strong><\/p>\n\n\n\n<p>Are you losing ground on one platform (e.g. Reddit) while winning somewhere else (e.g. on Instagram)?<\/p>\n\n\n\n<figure data-wp-context=\"{&quot;imageId&quot;:&quot;6a5a28f5e3ec1&quot;}\" data-wp-interactive=\"core\/image\" data-wp-key=\"6a5a28f5e3ec1\" class=\"wp-block-image size-full wp-lightbox-container\"><img loading=\"lazy\" decoding=\"async\" width=\"799\" height=\"491\" data-wp-class--hide=\"state.isContentHidden\" data-wp-class--show=\"state.isContentVisible\" data-wp-init=\"callbacks.setButtonStyles\" data-wp-on--click=\"actions.showLightbox\" data-wp-on--load=\"callbacks.setButtonStyles\" data-wp-on-window--resize=\"callbacks.setButtonStyles\" src=\"https:\/\/brand24.com\/blog\/app\/uploads\/2025\/09\/sentiment-analysis-platform-share-chart-1.png\" alt=\"\" class=\"wp-image-184785\" srcset=\"https:\/\/brand24.com\/blog\/app\/uploads\/2025\/09\/sentiment-analysis-platform-share-chart-1.png 799w, https:\/\/brand24.com\/blog\/app\/uploads\/2025\/09\/sentiment-analysis-platform-share-chart-1-18x12.png 18w, https:\/\/brand24.com\/blog\/app\/uploads\/2025\/09\/sentiment-analysis-platform-share-chart-1-300x184.png 300w, https:\/\/brand24.com\/blog\/app\/uploads\/2025\/09\/sentiment-analysis-platform-share-chart-1-248x152.png 248w, https:\/\/brand24.com\/blog\/app\/uploads\/2025\/09\/sentiment-analysis-platform-share-chart-1-90x55.png 90w\" sizes=\"auto, (max-width: 799px) 100vw, 799px\" \/><button\n\t\t\tclass=\"lightbox-trigger\"\n\t\t\ttype=\"button\"\n\t\t\taria-haspopup=\"dialog\"\n\t\t\taria-label=\"Enlarge\"\n\t\t\tdata-wp-init=\"callbacks.initTriggerButton\"\n\t\t\tdata-wp-on--click=\"actions.showLightbox\"\n\t\t\tdata-wp-style--right=\"state.imageButtonRight\"\n\t\t\tdata-wp-style--top=\"state.imageButtonTop\"\n\t\t>\n\t\t\t<svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"12\" height=\"12\" fill=\"none\" viewBox=\"0 0 12 12\">\n\t\t\t\t<path fill=\"#fff\" d=\"M2 0a2 2 0 0 0-2 2v2h1.5V2a.5.5 0 0 1 .5-.5h2V0H2Zm2 10.5H2a.5.5 0 0 1-.5-.5V8H0v2a2 2 0 0 0 2 2h2v-1.5ZM8 12v-1.5h2a.5.5 0 0 0 .5-.5V8H12v2a2 2 0 0 1-2 2H8Zm2-12a2 2 0 0 1 2 2v2h-1.5V2a.5.5 0 0 0-.5-.5H8V0h2Z\" \/>\n\t\t\t<\/svg>\n\t\t<\/button><figcaption class=\"wp-element-caption\">An example of how sentiment can be distributed across social and non-social media channels (Source: Brand24 tool)<\/figcaption><\/figure>\n\n\n\n<p><strong>3. Topic-level sentiment<\/strong><\/p>\n\n\n\n<p>When you fix a product issue, does negative sentiment in that topic decline?<\/p>\n\n\n\n<figure data-wp-context=\"{&quot;imageId&quot;:&quot;6a5a28f5e430d&quot;}\" data-wp-interactive=\"core\/image\" data-wp-key=\"6a5a28f5e430d\" class=\"wp-block-image size-large wp-lightbox-container\"><img loading=\"lazy\" decoding=\"async\" width=\"1140\" height=\"616\" data-wp-class--hide=\"state.isContentHidden\" data-wp-class--show=\"state.isContentVisible\" data-wp-init=\"callbacks.setButtonStyles\" data-wp-on--click=\"actions.showLightbox\" data-wp-on--load=\"callbacks.setButtonStyles\" data-wp-on-window--resize=\"callbacks.setButtonStyles\" src=\"https:\/\/brand24.com\/blog\/app\/uploads\/2025\/09\/sentiment-analysis-topic-sentiment-share-1-1140x616.png\" alt=\"\" class=\"wp-image-184786\" srcset=\"https:\/\/brand24.com\/blog\/app\/uploads\/2025\/09\/sentiment-analysis-topic-sentiment-share-1-1140x616.png 1140w, https:\/\/brand24.com\/blog\/app\/uploads\/2025\/09\/sentiment-analysis-topic-sentiment-share-1-18x10.png 18w, https:\/\/brand24.com\/blog\/app\/uploads\/2025\/09\/sentiment-analysis-topic-sentiment-share-1-300x162.png 300w, https:\/\/brand24.com\/blog\/app\/uploads\/2025\/09\/sentiment-analysis-topic-sentiment-share-1-248x134.png 248w, https:\/\/brand24.com\/blog\/app\/uploads\/2025\/09\/sentiment-analysis-topic-sentiment-share-1-90x49.png 90w, https:\/\/brand24.com\/blog\/app\/uploads\/2025\/09\/sentiment-analysis-topic-sentiment-share-1.png 1199w\" sizes=\"auto, (max-width: 1140px) 100vw, 1140px\" \/><button\n\t\t\tclass=\"lightbox-trigger\"\n\t\t\ttype=\"button\"\n\t\t\taria-haspopup=\"dialog\"\n\t\t\taria-label=\"Enlarge\"\n\t\t\tdata-wp-init=\"callbacks.initTriggerButton\"\n\t\t\tdata-wp-on--click=\"actions.showLightbox\"\n\t\t\tdata-wp-style--right=\"state.imageButtonRight\"\n\t\t\tdata-wp-style--top=\"state.imageButtonTop\"\n\t\t>\n\t\t\t<svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"12\" height=\"12\" fill=\"none\" viewBox=\"0 0 12 12\">\n\t\t\t\t<path fill=\"#fff\" d=\"M2 0a2 2 0 0 0-2 2v2h1.5V2a.5.5 0 0 1 .5-.5h2V0H2Zm2 10.5H2a.5.5 0 0 1-.5-.5V8H0v2a2 2 0 0 0 2 2h2v-1.5ZM8 12v-1.5h2a.5.5 0 0 0 .5-.5V8H12v2a2 2 0 0 1-2 2H8Zm2-12a2 2 0 0 1 2 2v2h-1.5V2a.5.5 0 0 0-.5-.5H8V0h2Z\" \/>\n\t\t\t<\/svg>\n\t\t<\/button><figcaption class=\"wp-element-caption\">An example of topic-level sentiment comparison. You can see that some BMW topics have much higher negative sentiment than others. (Source: Brand24 tool)<\/figcaption><\/figure>\n\n\n\n<p><strong>4. Competitor comparison<\/strong><\/p>\n\n\n\n<p>What&#8217;s your share of positive and negative voice relative to your rivals?<\/p>\n\n\n\n<figure data-wp-context=\"{&quot;imageId&quot;:&quot;6a5a28f5e476e&quot;}\" data-wp-interactive=\"core\/image\" data-wp-key=\"6a5a28f5e476e\" class=\"wp-block-image size-large wp-lightbox-container\"><img loading=\"lazy\" decoding=\"async\" width=\"1140\" height=\"725\" data-wp-class--hide=\"state.isContentHidden\" data-wp-class--show=\"state.isContentVisible\" data-wp-init=\"callbacks.setButtonStyles\" data-wp-on--click=\"actions.showLightbox\" data-wp-on--load=\"callbacks.setButtonStyles\" data-wp-on-window--resize=\"callbacks.setButtonStyles\" src=\"https:\/\/brand24.com\/blog\/app\/uploads\/2025\/09\/sentiment-analysis-competitor-comparison-1-1140x725.png\" alt=\"\" class=\"wp-image-184787\" srcset=\"https:\/\/brand24.com\/blog\/app\/uploads\/2025\/09\/sentiment-analysis-competitor-comparison-1-1140x725.png 1140w, https:\/\/brand24.com\/blog\/app\/uploads\/2025\/09\/sentiment-analysis-competitor-comparison-1-18x12.png 18w, https:\/\/brand24.com\/blog\/app\/uploads\/2025\/09\/sentiment-analysis-competitor-comparison-1-300x191.png 300w, https:\/\/brand24.com\/blog\/app\/uploads\/2025\/09\/sentiment-analysis-competitor-comparison-1-248x159.png 248w, https:\/\/brand24.com\/blog\/app\/uploads\/2025\/09\/sentiment-analysis-competitor-comparison-1-90x57.png 90w, https:\/\/brand24.com\/blog\/app\/uploads\/2025\/09\/sentiment-analysis-competitor-comparison-1.png 1200w\" sizes=\"auto, (max-width: 1140px) 100vw, 1140px\" \/><button\n\t\t\tclass=\"lightbox-trigger\"\n\t\t\ttype=\"button\"\n\t\t\taria-haspopup=\"dialog\"\n\t\t\taria-label=\"Enlarge\"\n\t\t\tdata-wp-init=\"callbacks.initTriggerButton\"\n\t\t\tdata-wp-on--click=\"actions.showLightbox\"\n\t\t\tdata-wp-style--right=\"state.imageButtonRight\"\n\t\t\tdata-wp-style--top=\"state.imageButtonTop\"\n\t\t>\n\t\t\t<svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"12\" height=\"12\" fill=\"none\" viewBox=\"0 0 12 12\">\n\t\t\t\t<path fill=\"#fff\" d=\"M2 0a2 2 0 0 0-2 2v2h1.5V2a.5.5 0 0 1 .5-.5h2V0H2Zm2 10.5H2a.5.5 0 0 1-.5-.5V8H0v2a2 2 0 0 0 2 2h2v-1.5ZM8 12v-1.5h2a.5.5 0 0 0 .5-.5V8H12v2a2 2 0 0 1-2 2H8Zm2-12a2 2 0 0 1 2 2v2h-1.5V2a.5.5 0 0 0-.5-.5H8V0h2Z\" \/>\n\t\t\t<\/svg>\n\t\t<\/button><figcaption class=\"wp-element-caption\">An example of sentiment comparison between two competitors, Claude and ChatGPT (Source: Brand24 tool)<\/figcaption><\/figure>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"benefits\">Benefits of sentiment analysis [+ real examples]<\/h2>\n\n\n\n<p>Sentiment analysis can deliver very different, measurable <a href=\"https:\/\/brand24.com\/blog\/tag\/benefits-of-sentiment-analysis\/\" title=\"benefits of sentiment analysis\">benefits<\/a> depending on your industry. <\/p>\n\n\n\n<p>Here are four real-world results that show how it works in practice.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"restaurants\">Sentiment analysis for Food &amp; Beverage \/ Restaurants<\/h3>\n\n\n\n<p><strong>\ud83c\udfaf<\/strong> <strong>Key benefits for this use case:<\/strong><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Customer feedback at scale:<\/strong> understand what guests think about specific menu items, service quality, and atmosphere without reading every review manually<\/li>\n\n\n\n<li><strong>New market demand discovery:<\/strong> track mentions from cities where you don&#8217;t have a location yet \u2014 organic demand is often the best expansion signal<\/li>\n\n\n\n<li><strong>Influencer ROI measurement:<\/strong> correlate reach data from influencer collaborations with actual sentiment and business outcomes<\/li>\n\n\n\n<li><strong>Campaign effectiveness:<\/strong> measure whether your marketing content is driving positive brand associations<\/li>\n<\/ul>\n\n\n\n<p>\ud83c\udfc6<strong>Real-life example \u2014 Pasibus:<\/strong><\/p>\n\n\n\n<p><strong>Pasibus<\/strong> \u2014 a fast-casual burger brand that developed into one of Poland&#8217;s most recognized food brands \u2014 uses Brand24 daily for sentiment monitoring, influencer tracking, and customer insight.<\/p>\n\n\n\n<p>One of their most creative uses: <strong>they track mentions from cities where Pasibus doesn&#8217;t yet have a location.<\/strong> When fans in a new city start organically asking <em>&#8220;when is Pasibus opening here?&#8221;<\/em>, that becomes a data point in expansion planning.<\/p>\n\n\n\n<p>AVE has been a core annual marketing KPI for the Pasibus team for three consecutive years, and using <a href=\"https:\/\/brand24.com\/blog\/best-sentiment-analysis-tools\/\">sentiment analysis tool <\/a>is what drives the feedback loop that keeps improving content quality.<\/p>\n\n\n\n<p class=\"has-background\" style=\"background-color:#e8f4ee\">\n\ud83d\udcda See Pasibus&#8217;s success story: <a href=\"https:\/\/brand24.com\/case-study\/pasibus\/\" target=\"_blank\" rel=\"nofollow noopener noreferrer\">How Pasibus Uses Brand24 to Understand Its Customers&#8217; Needs\n\n <\/a><\/p>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"finance\">Sentiment analysis for Finance &amp; Trading<\/h3>\n\n\n\n<p><strong>\ud83c\udfaf<\/strong> <strong>Key benefits for this use case:<\/strong><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Competitor intelligence: <\/strong>detect negative sentiment about competitors&#8217; products and act on it faster than they can<\/li>\n\n\n\n<li><strong>Market mood signals: <\/strong>understand how investors feel about market events in real time<\/li>\n\n\n\n<li><strong>Reputation protection in a high-trust industry:<\/strong> catch negative mentions early, when they&#8217;re still manageable<\/li>\n\n\n\n<li><strong>Content strategy:<\/strong> identify trending topics and investor concerns to inform market analysis and reports<\/li>\n<\/ul>\n\n\n\n<p>\ud83c\udfc6 <strong>Real case study \u2014 XTB:<\/strong><\/p>\n\n\n\n<p>XTB is a global trading platform operating in multiple markets. Szymon Szymanski, XTB&#8217;s Chief Growth Officer, calls sentiment analysis his favorite Brand24 feature \u2014 because it gives a clear picture of how XTB is perceived by customers across regions.<\/p>\n\n\n\n<p><strong>The results speak for themselves:<\/strong> in Q3 2024, XTB gained <strong>108,104 new clients<\/strong> with active clients reaching <strong>474,117, up 69% year-over-year.<\/strong> It was a <strong>60% jump from the previous year<\/strong>! <\/p>\n\n\n\n<p>While Brand24 is one part of a larger growth strategy, competitive intelligence from sentiment monitoring \u2014 including the counter-campaign example above \u2014 was a direct contributor.<\/p>\n\n\n\n<p class=\"has-background\" style=\"background-color:#e8f4ee\">\n\ud83d\udcda See XTB&#8217;s success story: <a href=\"https:\/\/brand24.com\/case-study\/xtb\/\" target=\"_blank\" rel=\"nofollow noopener noreferrer\">How XTB Uses Brand24 to Dominate the Online Trading Market\n\n <\/a><\/p>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"entertainment\">Sentiment analysis for Entertainment &amp; Gaming<\/h3>\n\n\n\n<p><strong>\ud83c\udfaf<\/strong> <strong>Key benefits for this use case:<\/strong><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Post-event analysis: <\/strong>understand audience sentiment to individual events, streams, or content drops in real time<\/li>\n\n\n\n<li><strong>Sentiment by platform: <\/strong>gaming audiences behave differently on TikTok vs. X \u2014 tracking by channel tells you where to focus<\/li>\n\n\n\n<li><strong>Community health monitoring: <\/strong>catch negative sentiment spikes that might indicate community friction before they escalate<\/li>\n\n\n\n<li><strong>Limited-edition engagement tracking: <\/strong>see how audiences respond to new skins, in-game items, or content updates<\/li>\n<\/ul>\n\n\n\n<p>\ud83c\udfc6 <strong>Real success story \u2014 Twitch:<\/strong><\/p>\n\n\n\n<p><strong>Twitch<\/strong>, the live streaming platform, <span style=\"box-sizing: border-box; margin: 0px; padding: 0px;\">use<\/span>s <a href=\"https:\/\/brand24.com\/media-monitoring-software\/\" target=\"_blank\" rel=\"noopener\" title=\"\">media monitoring software<\/a> to track social chatter and gain customer insights after every major event. <\/p>\n\n\n\n<p>Their monthly reporting format captures both reach <strong>(33M social media reach in one December report)<\/strong> and sentiment split <strong>(63% positive vs. 37% negative)<\/strong>, letting the team immediately identify which events and content types generate the most positive audience sentiment.<\/p>\n\n\n<div class=\"acf-testimonial acf-testimonial--default\">\n                    <div class=\"acf-testimonial__answer\">Social media mentions and the associated sentiment scores are the most useful KPI for us because we can at a glance understand what is going on in a given month and have the opportunity to dig deeper if needed.\r\n\r\n<\/div>\n        <div class=\"acf-testimonial__row\">\n                <div class=\"acf-testimonial__author-content\">\n                            <div class=\"acf-testimonial__author-name\">Twitch team                            <\/div>\n                                <\/div>\n    <\/div>\n    <\/div>\n\n\n\n<p>The detailed mention view is Twitch&#8217;s most-used feature: &#8220;I can get a better understanding of what is the current conversation around our brand,&#8221; says their Brand24 user.<\/p>\n\n\n\n<p class=\"has-background\" style=\"background-color:#e8f4ee\">\n\ud83d\udcda See Twitch&#8217;s success story: <a href=\"https:\/\/brand24.com\/case-study\/twitch\/\" target=\"_blank\" rel=\"nofollow noopener noreferrer\">How Does Twitch use Brand24 to find customer&#8217;s insights?\n\n\n <\/a><\/p>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"media\">Sentiment analysis for Media &amp; Podcasts<\/h3>\n\n\n\n<p>\ud83c\udfaf <strong>Key benefits for this use case:<\/strong><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Per-episode performance: <\/strong>understand which episodes generate the most positive response \u2014 and why<\/li>\n\n\n\n<li><strong>Audience segmentation: <\/strong>identify different sentiment profiles among different listener communities<\/li>\n\n\n\n<li><strong>Influencer and partner discovery: <\/strong>find high-reach authors talking positively about your content<\/li>\n\n\n\n<li><strong>Genre and topic signals: <\/strong>understand which content directions generate the strongest emotional engagement<\/li>\n<\/ul>\n\n\n\n<p>\ud83c\udfc6 <strong>Real example \u2014 Wondery:<\/strong><\/p>\n\n\n\n<p><strong>Wondery<\/strong>, one of the world&#8217;s leading podcast networks, uses Brand24&#8217;s Sentiment and Reach Analysis to evaluate the performance of individual episodes. <\/p>\n\n\n\n<p>By tracking sentiment for each episode, the team can see how many people are talking about the podcast and what they think of it. <\/p>\n\n\n\n<p><span style=\"box-sizing: border-box; margin: 0px; padding: 0px;\">Such<a href=\"https:\/\/brand24.com\/market-insights\/\" target=\"_blank\">&nbsp;market insight<\/a><\/span><strong>s<\/strong>&nbsp;help identify what the audience likes, spot key influencers, and guide what content to create next.<\/p>\n\n\n\n<p class=\"has-background\" style=\"background-color:#e8f4ee\">\n\ud83d\udcda See Wondery&#8217;s success story: <a href=\"https:\/\/brand24.com\/case-study\/wondery\/\" target=\"_blank\" rel=\"nofollow noopener noreferrer\">How Wondery Analyzes The Success of Each Podcast and Identify Influential Listeners\n\n\n <\/a><\/p>\n\n\n\n<div class=\"acf-simple-cta acf-simple-cta--default acf-simple-cta--no-icon acf-simple-cta--small\">\n    <div class=\"acf-simple-cta__wrapper\">\n        <div class=\"acf-simple-cta__row\">\n            <div class=\"acf-simple-cta__content\">\n                                                    <div class=\"acf-simple-cta__title\">Start Sentiment Analysis Now!<\/div>\n                            <\/div>\n                            <a href=\"https:\/\/app.brand24.com\/user\/register-account\/?custom_form=118\" class=\"acf-simple-cta__btn\" target=\"\">Start Trial!<\/a>\n                    <\/div>\n    <\/div>\n<\/div>\n\n\n\n<div class=\"wp-block-b24-faq b24-faq\"><h2 class=\"b24-faq__header\">FAQ<\/h2><div class=\"b24-faq__items\">\n<div class=\"wp-block-b24-faq-item b24-faq__item\"><h3 class=\"b24-faq__question\"><button class=\"b24-faq__toggle\" type=\"button\" aria-expanded=\"false\"><span class=\"b24-faq__question-text\">What is sentiment analysis?<\/span><span class=\"b24-faq__toggle-icon-container\" aria-hidden=\"true\"><span class=\"b24-faq__toggle-icon\" aria-hidden=\"true\"><\/span><\/span><\/button><\/h3><div class=\"b24-faq__answer\">\n<p>Sentiment analysis is a <strong>natural language processing (NLP) <\/strong>technique that classifies written content as positive, negative, or neutral. More advanced tools also detect specific <strong>emotions<\/strong> (joy, anger, fear), <strong>customer intent<\/strong> (complaint, praise, purchase interest), and <strong>aspect-level sentiment<\/strong> (which feature or topic specifically is positive or negative).<\/p>\n<\/div><\/div>\n\n\n\n<div class=\"wp-block-b24-faq-item b24-faq__item\"><h3 class=\"b24-faq__question\"><button class=\"b24-faq__toggle\" type=\"button\" aria-expanded=\"false\"><span class=\"b24-faq__question-text\">What is the difference between sentiment analysis and emotion analysis?<\/span><span class=\"b24-faq__toggle-icon-container\" aria-hidden=\"true\"><span class=\"b24-faq__toggle-icon\" aria-hidden=\"true\"><\/span><\/span><\/button><\/h3><div class=\"b24-faq__answer\">\n<p><strong>Sentiment analysis<\/strong> determines polarity \u2014 whether content is positive, negative, or neutral. <strong>Emotion analysis <\/strong>goes deeper, identifying the specific feeling behind that polarity: joy, sadness, anger, fear, disgust, or admiration. <\/p>\n<\/div><\/div>\n\n\n\n<div class=\"wp-block-b24-faq-item b24-faq__item\"><h3 class=\"b24-faq__question\"><button class=\"b24-faq__toggle\" type=\"button\" aria-expanded=\"false\"><span class=\"b24-faq__question-text\">How to use AI for sentiment analysis?<\/span><span class=\"b24-faq__toggle-icon-container\" aria-hidden=\"true\"><span class=\"b24-faq__toggle-icon\" aria-hidden=\"true\"><\/span><\/span><\/button><\/h3><div class=\"b24-faq__answer\">\n<p>Set up a project in a sentiment analysis tool with your brand name and relevant keywords. Use the Topic Analysis to see which subjects drive sentiment, the Emotion Analysis to detect specific feelings, and the AI Insights to surface recommendations. Always manually review key mention clusters before making high-stakes decisions.<\/p>\n<\/div><\/div>\n\n\n\n<div class=\"wp-block-b24-faq-item b24-faq__item\"><h3 class=\"b24-faq__question\"><button class=\"b24-faq__toggle\" type=\"button\" aria-expanded=\"false\"><span class=\"b24-faq__question-text\">What is neutral sentiment in sentiment analysis?<\/span><span class=\"b24-faq__toggle-icon-container\" aria-hidden=\"true\"><span class=\"b24-faq__toggle-icon\" aria-hidden=\"true\"><\/span><\/span><\/button><\/h3><div class=\"b24-faq__answer\">\n<p>A neutral sentiment in sentiment analysis means the text expresses no clear positive or negative emotional tone \u2014 it&#8217;s informational, descriptive, or objective. <\/p>\n\n\n\n<p>For example, <em>&#8220;Brand24 released a new feature update&#8221;<\/em> is neutral. <\/p>\n\n\n\n<p>In Brand24&#8217;s 2026 research on the sentiment analysis conversation itself, <strong>94% of marketing-context mentions were classified as neutral<\/strong>, reflecting the educational, descriptive nature of most marketing content.<\/p>\n<\/div><\/div>\n\n\n\n<div class=\"wp-block-b24-faq-item b24-faq__item\"><h3 class=\"b24-faq__question\"><button class=\"b24-faq__toggle\" type=\"button\" aria-expanded=\"false\"><span class=\"b24-faq__question-text\">How can sentiment analysis be used to improve customer experience?<\/span><span class=\"b24-faq__toggle-icon-container\" aria-hidden=\"true\"><span class=\"b24-faq__toggle-icon\" aria-hidden=\"true\"><\/span><\/span><\/button><\/h3><div class=\"b24-faq__answer\">\n<p>Sentiment analysis identifies what customers are frustrated about in real time. When a sentiment analysis tool detects recurring negative mentions around a specific topic, those signals can be shared with product teams to fix the problem. <\/p>\n\n\n\n<p>The result: monitoring surfaces complaints, teams fix issues, negative mentions drop, and sentiment improves.<\/p>\n<\/div><\/div>\n\n\n\n<div class=\"wp-block-b24-faq-item b24-faq__item\"><h3 class=\"b24-faq__question\"><button class=\"b24-faq__toggle\" type=\"button\" aria-expanded=\"false\"><span class=\"b24-faq__question-text\">Which sentiment analysis tool is best?<\/span><span class=\"b24-faq__toggle-icon-container\" aria-hidden=\"true\"><span class=\"b24-faq__toggle-icon\" aria-hidden=\"true\"><\/span><\/span><\/button><\/h3><div class=\"b24-faq__answer\">\n<p>The best sentiment analysis tool depends on your use case:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Brand24<\/strong> is the best choice for brands that need real-time monitoring combined with AI-powered sentiment, emotion, and topic analysis. <\/li>\n\n\n\n<li><strong>Brandwatch<\/strong> and <strong>Sprout<\/strong> <strong>Social<\/strong> are frequently cited in our research for enterprise-scale use cases. <\/li>\n\n\n\n<li><strong>Meltwater<\/strong> leads in earned media and PR monitoring. <\/li>\n<\/ul>\n<\/div><\/div>\n\n\n\n<div class=\"wp-block-b24-faq-item b24-faq__item\"><h3 class=\"b24-faq__question\"><button class=\"b24-faq__toggle\" type=\"button\" aria-expanded=\"false\"><span class=\"b24-faq__question-text\">How to use sentiment analysis for brand building?<\/span><span class=\"b24-faq__toggle-icon-container\" aria-hidden=\"true\"><span class=\"b24-faq__toggle-icon\" aria-hidden=\"true\"><\/span><\/span><\/button><\/h3><div class=\"b24-faq__answer\">\n<p>Use sentiment analysis to track how your brand is perceived online, flag reputation risks early, see which campaign messages connect emotionally, identify top advocates, and compare sentiment with competitors. Monitoring sentiment ratios over time shows if perception is shifting and if your marketing strategy is working.<\/p>\n<\/div><\/div>\n\n\n\n<div class=\"wp-block-b24-faq-item b24-faq__item\"><h3 class=\"b24-faq__question\"><button class=\"b24-faq__toggle\" type=\"button\" aria-expanded=\"false\"><span class=\"b24-faq__question-text\">What is NLP sentiment analysis?<\/span><span class=\"b24-faq__toggle-icon-container\" aria-hidden=\"true\"><span class=\"b24-faq__toggle-icon\" aria-hidden=\"true\"><\/span><\/span><\/button><\/h3><div class=\"b24-faq__answer\">\n<p><strong>Natural language processing (NLP)<\/strong> is the underlying technology that enables computers to understand human language. <\/p>\n\n\n\n<p>In sentiment analysis, NLP algorithms analyze text structure, context, and meaning to classify sentiment. Modern NLP-based sentiment analysis uses transformer models (like BERT, RoBERTa, and DeBERTa) that can capture nuanced language patterns, including context-dependent meaning.<\/p>\n<\/div><\/div>\n<\/div><\/div>\n","protected":false},"excerpt":{"rendered":"<p>85% of customers drop brands over a single issue! This guide covers what sentiment analysis is, how AI-powered tools work, based on Brand24&#8217;s original research of 12,894 mentions.<\/p>\n","protected":false},"author":74,"featured_media":144645,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":"","_links_to":"","_links_to_target":""},"categories":[3822],"tags":[2395,2326,2323,2392],"class_list":["post-109840","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-sentiment-analysis","tag-how-to-do-sentiment-analysis","tag-sentiment-analysis","tag-sentiment-analysis-tools","tag-what-is-sentiment-analysis"],"acf":[],"aioseo_notices":[],"aioseo_head":"\n\t\t<!-- All in One SEO 4.9.8 - aioseo.com -->\n\t<meta name=\"description\" content=\"Brand24 analyzed 12,894 mentions to map how sentiment analysis is used in 2026. 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