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We Analyzed 1.3M ChatGPT Mentions: Here’s What We Found
In February 2026, ChatGPT hit a massive milestone: 900 million weekly active users. At the same time, it was being mentioned somewhere online every 4 seconds!
We analyzed 1.3M ChatGPT mentions using social listening and media monitoring data to understand how people use the tool, what drives the conversation, and how sentiment around ChatGPT changes over time.
What we found: Almost 8 out of 10 times (79%) mentions of ChatGPT focus on real use cases, and those practical discussions generate 4-18x more positive sentiment than the general chatter about AI.
Key takeaways:
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79% of the conversation is about use cases, not the ethical questions
When people mention ChatGPT, almost 80% are focusing on practical use, like coding help, speeding up their workflow, or everyday tasks. The deep conversations about ethics are happening too, but they’re not the main topic most of the time.
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Negative buzz shot up 58% in just six weeks, and the tool wasn't to blame
That big jump in negativity was fast, even though the ChatGPT product itself was pretty much the same. What triggered it were the OpenAI controversies, not bad user experience.
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When people talk about actual uses, they're 4-18x more positive
If the conversation is about a specific, real-world task, like using AI to make an image or draft an email, people feel much more positive about it than when they just talk about "AI" in general.
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People trust the product, but not always the company
Users are clearly drawing a line between ChatGPT (the tool) and OpenAI (the company). Most negative spikes came from decisions the company made, not problems with the AI itself. This shows that having a great product might not be enough to fully protect your brand reputation.
ChatGPT generates more online conversation than some countries generate news
Hitting a reach of 12.7 billion in just 2 months speaks a lot about ChatGPT’s massive cultural impact.
In January and February 2026 alone, people posted, shared, argued about, and reacted to ChatGPT 1.3 million times.
In February 2026, OpenAI announced ChatGPT had topped 900 million weekly active users, up from 800 million just four months earlier.
That 12.5% growth jump, starting from an already huge user base, created a ton of media coverage, which kept the mention volume high through the period.
What do people focus on when they mention ChatGPT?
It’s probably not what you’d expect. Most of the chatter is focused on practical, professional ways to use it, rather than big ethical debates, at least when you look at the volume of brand mentions.
79% of the share of voice goes to the topic of “AI Tools and Applications”:
- 1 coding
- 2 boosting productivity
- 3 improving business workflows
- 4 comparing LLM models
- 5 API integrations
Entertainment like memes, viral trends, and fun experiments comes in second at 11% of share of voice.
As for the heavy, “is-this-the-end-of-the-world-as-we-know-it” topics (AI safety, ethics, or rules), they barely show up as a separate conversation.
That said, a bit of that worry does pop up as negative comments within the discussions about the AI tools themselves.
Looking closely at the numbers in the table, the sentiment tells an interesting story:
- 1 The "AI Tools" category (which is the largest one we looked at) actually had the most negative sentiment – 13.7%.
- 2 On the other hand, even though "Entertainment" content was “only” 11% of the chat, it had the highest positive sentiment at 30%.
ChatGPT analysis shows that 79% of use case conversations are about work
When we filtered the data down to mentions where people talked specifically about how they use ChatGPT (that’s 258.3 thousand mentions out of 1.3 million total), a clear pattern showed up in the social listening data.
Professional and business productivity dominated with 78% of reach, followed by:
- 1 content creation
- 2 AI image generation
- 3 marketing & SEO
- 4 travel planning
- 5 education and learning
- 6 healthcare applications
This is interesting from a brand sentiment perspective, because use case discussions are more positive than general chatter about AI: the sentiment was 18.5% positive compared to 17% overall.
Basically, when people are sharing what they’re actually getting done with the tool, the tone of brand mentions shifts: they’re a little happier than when they’re just debating what AI means for the world.
Global go-to professional AI helper
People are mainly using ChatGPT to boost their professional life in these ways – something that shows up very clearly in social listening insights:
- 1 daily workflow automation
- 2 getting a fresh perspective while brainstorming
- 3 technical problem-solving
- 4 writing and improving software code
- 5 building custom GPTs for specific business needs
Automation through the integrations with tools like Make or Zapier came up a lot, which suggests ChatGPT is becoming more and more naturally used in existing software stacks.
Less common ways people use it: travel, religious content, companionship
Three specific areas popped up that were less common than professional use but really interesting from a social media analytics perspective:
Travel planning
People are talking about getting amazingly detailed help with their trips. The most mentioned use cases were:
- 1 Day trip planning
- 2 Multi-day itineraries
- 3 Destination recommendations
- 4 Activity scheduling and optimization
Religious content generation
There were also plenty of posts mentioning AI-generated content tied to Hindu religious themes, festivals, and cultural celebrations like Holi.
Companionship
There’s a quiet but growing group of people building long, meaningful relationships with ChatGPT. Analysis of mentions shows that one example has lasted 18 months, with a woman saying she felt “too invested to delete him.”
73% of mentions were neutral, but negative sentiment spiked
Most mentions of ChatGPT (73%) are pretty neutral. That’s how most people talk about it online: just sharing information like:
- 1 what prompts they used
- 2 how the outputs compare
- 3 or posting tutorials and results
And all this without adding any strong emotional judgment.
However, the mentions with a clear feeling are interesting. Positive mentions (17%) beat negative ones (10%).
The sentiment, though, was not really a static metric here.
There was a big 58% jump in negative sentiment over just six weeks.
This wasn’t caused by one big event, but it happened during a period with a few controversies that all piled up in February:
- 1 the Canada shooting incident (Feb 8–11)
- 2 the issues with the Pentagon deal
- 3 the uproar over an advertising announcement
- 4 debate about how much energy ChatGPT uses
ChatGPT popularity is different on each platform
The platform analysis shows that where people are talking about something matters more than the topic itself when it comes to how they feel.
And it’s something that becomes very clear when you look at social media montitoring data and break down brand mentions sentiment by source:
- 1 People on Instagram tend to be super excited about their AI-generated items.
- 2 X (Twitter) users are all over the place: some love it, some deeply hate it.
- 3 News outlets are leaning toward being skeptical, often shaping broader brand perception.
- 4 And Reddit users? They're mostly interested in breaking ChatGPT down and analyzing it in dozens of subreddits.
ChatGPT sentiment looks different on every platform
Same OpenAI brand, same ChatGPT product, and completely different stories depending on where you look:
Here’s what’s driving ChatGPT popularity and sentiment on the TOP 5 channels (by share of voice):
01 Instagram: The most positive of all channels
Key characteristics:
- 1 Visual trends took the lead: caricature challenge, AI photo generation, and posts with profile pic updates
- 2 A lot of high-engagement content: especially personal AI-made images and creative use-case examples
- 3 Positive drivers: strong entertainment value, room for creative expression, and viral challenges people wanted to join
Sentiment indicators:
- 1 Visual/creative trends typically generate positive engagement
- 2 Personal success stories with AI tools
- 3 Entertainment-focused usage
- 4 Lower controversy compared to news/Twitter
02 X (Twitter): The most polarized channel
Key characteristics:
- 1 Tech-savvy audience: Deep discussions about AI capabilities and limitations
- 2 Political discussions: Pentagon deal controversy, data privacy concerns and worries
- 3 Competitive comparisons: ChatGPT vs. Claude, Gemini, DeepSeek
- 4 Corporate criticism: OpenAI business decisions, ChatGPT advertising announcements
Positive sentiment drivers:
- 1 Technical achievements and capabilities
- 2 Productivity use cases
- 3 Tool recommendations and tutorials
Negative sentiment drivers:
- 1 Ethical concerns
- 2 Corporate decisions
- 3 Political affiliations
- 4 Privacy and surveillance concerns
03 News Media: From mixed to mostly negative sentiment
Key characteristics:
- 1 Corporate news: OpenAI business developments, advertising initiatives
- 2 Safety concerns: Canada shooting incident and lack of law enforcement notification
- 3 Policy discussions: AI regulation, government partnerships
- 4 Ethical debates: Energy consumption, environmental impact
Negative news coverage:
- 1 Canada shooting controversy (February 25, 2026)
- 2 Advertising announcement critique
- 3 Energy consumption debate
Positive news coverage:
- 1 ChatGPT user growth milestones (900M weekly active users)
- 2 Technical advancements and new features
- 3 User- and business success stories and practical applications
04 Other Socials: Full of detailed discussions and mixed sentiment
Key characteristics:
- 1 In-depth discussions: Technical limitations, use case analysis
- 2 Community support: Troubleshooting, tips, and tricks
- 3 Skeptical perspective: Critical evaluation of AI capabilities
- 4 Honest feedback: Both successes and failures shared
Positive sentiment drivers:
- 1 Helpful community sharing prompts and techniques
- 2 Success stories with specific use cases
- 3 Technical appreciation for capabilities
Negative sentiment drivers:
- 1 Communication criticism
- 2 Frustration with limitations
- 3 Concerns about over-reliance on AI
- 4 Critical analysis of AI-generated content quality
05 TikTok: Much entertainment-focused with mixed sentiment
Key characteristics:
- 1 Tutorial content: How-to videos for AI prompts
- 2 Meme culture: Humorous takes on AI interactions
- 3 Trend participation: Viral challenges and creative content
- 4 Educational content: Quick tips and productivity hacks
Positive sentiment drivers:
- 1 Productivity prompts and life hacks
- 2 Creative applications showcase
- 3 Entertainment value
Negative sentiment drivers:
- 1 Fails and mishaps with AI
- 2 Humorous criticism
- 3 Trend backlash content
Negative sentiment came from both spikes and ongoing frustration
We found 10 different groups of controversial comments in the data.
Three of those groups generated higher reach and a lot of negative sentiment.
The other seven aren’t as big, but they kept popping up in the discussions about eroding user trust.
01 Canada shooting & OpenAI’s failure to report
This was the most significant of the controversial events in the whole set of data. A gunman in British Columbia had his ChatGPT account shut down for policy violations, but OpenAI never notified law enforcement.
This event caused the largest jump in negative sentiment and was behind most of that 58% spike in negative sentiment for the analyzed period.
02 Pentagon deal backlash
When OpenAI declared a partnership with the U.S. Department of Defense, people on social media got really upset and started a boycott.
Users publicly announced they were quitting the service, and the whole situation quickly became a major political issue.
Our data clearly showed that people were actively discussing switching to competitors like Claude, Gemini, and DeepSeek.
03 The “sickeningly evil” comment
OpenAI leadership compared how much energy ChatGPT uses to what it takes to “grow a person”, which some critics thought was a “sickeningly evil” way to put it.
The controversy highlighted the growing worries about the carbon footprint of AI data centers, an issue that’s been bubbling up since December 2025.
A negative headline went viral, the company’s leadership struggled to communicate effectively, and environmental critics amplified the story globally.
The most viral ChatGPT content wasn’t about work
Believe it or not, the time when people were most hyped about ChatGPT in the first two months of 2026 wasn’t because of some big product news or company announcement.
Instead, the biggest moment was all about fun: people asking ChatGPT to draw funny caricatures of them!
The peak day for chatter was February 9, 2026, when the Caricature Challenge blew up.
People were asking ChatGPT to generate exaggerated versions of themselves using prompts like: “Create a caricature of me and my job based on everything you know about me.”
They shared the results across social media using hashtags like #chatgpt, #trend, and #caricature, turning it into a full-on viral moment.
The content spread fast, driving a surge in visibility and brand awareness, even if not everyone was impressed with the results.
People like ChatGPT more when it helps them personally
When we broke down sentiment by discussion type and compared specific use cases with broader AI topics using social listening data, the gap was hard to miss:
- 1 Personal, low-stakes, specific use cases generate clearly positive brand sentiment.
- 2 Broader, high-stakes, professional and abstract discussions about AI tend to be a bit more negative.
When someone says something along the lines of, “I used ChatGPT and…,” the tone of those brand mentions is usually enthusiastic.
On the other hand, when the conversation shifts to “AI is changing [this or that]…” the sentiment becomes more anxious and defensive.
From a sentiment analysis perspective, it’s the same brand and product, but a completely different emotional response depending on how the topic is framed.
What this means if you’re a marketer in 2026
01 Monitor platforms separately, not as one score
People talk about ChatGPT very differently on different channels. On Instagram, it might be all about fun and creativity. On Twitter, it often becomes a hot topic for political debate.
Same product, but your audience is having completely different experiences.
If you’re doing media monitoring or social listening, analyzing only the overall sentiment score will only blur the picture.
02 Corporate decisions can be the #1 trust killer
The biggest spikes in negative brand mentions this year happened because of OpenAI’s choices, like Pentagon deals or announcing new ad policies. People complained about the product too, but those complaints were usually less intense.
When a company messes up with its core decisions, the damage to brand reputation can be quicker and deeper.
📚 Further read: How to Measure Brand Reputation
03 Show what people did, not what AI can do
Talking about specific, real-world examples with results people can see and share gets way more positive sentiment (from 4 to 18x more) than just talking generally about “AI’s potential.”
Sharing a “before-and-after” story is always better than just announcing a new feature.
04 The emotional relationship with AI is becoming real
We’re seeing a trend where people are getting attached to and forming emotional relationships with AI.
These conversations are already showing up in social listening insights, and they open up new questions around product design, communication, and even brand perception strategies.
05 TikTok and Instagram are your positive sentiment engines
TikTok has the highest positive sentiment share (27.4%) and Instagram generates the largest share of positive brand mentions for ChatGPT.
If you want to influence brand awareness metrics and balance more negative spaces like X (Twitter), this is where positive narratives actually scale.
📚 Further read: Brand Awareness Strategy [The Ultimate Guide for 2026]
Put your energy into visual content that clearly shows how your product helps people in real life and how they can use it day to day.
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