6,000 app reviews suggest people judge AI helpers and companions by different standards
Task usefulness dominated ChatGPT reviews while conversation and companionship dominated Replika reviews. The study analyses public review text—not representative users, wellbeing or product quality.
The short version
- What happened
- Researchers analysed 6,000 public app-store reviews: 3,000 for ChatGPT and 3,000 for Replika, using sentiment, emotion, topic modelling and statistical tests.
- Who it affects
- Designers and regulators may need different evaluation questions for an assistant that promises efficient work and a chatbot marketed around companionship. A five-star score alone can hide whether the user expected accuracy, emotional continuity or both.
- What remains unproven
- Self-selected public reviews
Keep in mind
Self-selected public reviews
3,000 reviews per app
Two apps only
Different sampling periods
Products changed over time
Lexicon-based emotion inference
Small effect sizes for emotion differences
No demographic, behavioural or wellbeing outcomes
Source analysis · 1 linked source. Primary analysed source date: 28 October 2026.
Read the full report · 3 min The evidence, methods, implications and limitations
Purpose showed up more clearly than overall positivity
A task assistant and a companion chatbot may both look conversational, but reviewers wrote about them as different kinds of products. The researchers sampled 3,000 public reviews for each app, then compared star ratings, sentiment words, emotion labels and topics.
The clearest split was what people discussed. Conversation and companionship accounted for 53.6% of Replika reviews and 10.9% of ChatGPT reviews. Task assistance and usefulness accounted for 30.9% of ChatGPT reviews and 1.2% of Replika reviews. ChatGPT ratings were also more concentrated at one and five stars, while Replika had more middle ratings.[1]
Review language is not a user-outcome study
The two sentiment methods did not agree on which app's reviews were more positive, and reported emotion differences were small. That makes broad claims about satisfaction inappropriate. The study instead supports a narrower point: people may evaluate instrumental and relational systems through different expectations.
Public reviewers are self-selecting, the products and policies change, and the two samples span different periods. The analysis did not verify reviewers' demographics, usage intensity, subscription status or mental-health outcomes. It compared two prominent apps rather than establishing universal categories for conversational AI.[1]
The distinction that matters
Two review frames, not two measures of product quality
The study found a strong topic split while overall sentiment remained method-sensitive.
Task frame
Reviewers discuss help and usefulness
30.9% of ChatGPT reviews; 1.2% of Replika reviews
Relationship frame
Reviewers discuss conversation and companionship
53.6% of Replika reviews; 10.9% of ChatGPT reviews
Evidence limit
Analyse posted review text
No representative user or wellbeing measure