mlsanityData to 14 Oct 2026

Expectation, Backlash, Recovery, and Excitement: How Model Releases Shape Reddit Perceptions of Conversational AI Systems

arXiv 2608.24654 ↗First posted 25 Aug 2026cs.CL cs.CYcited by 0

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Abstract (arXiv)

Conversational AI systems (CAISes) continuously change through model releases, feature updates, safety interventions, and access-policy shifts, yet user perceptions are often studied as static snapshots. We conduct a long-term, large-scale analysis of Reddit discussions to examine how users perceive CAIS model release interventions across providers. By combining sentiment classification and thematic concept analysis, we show that CAIS perceptions are dynamic and intervention-sensitive. Anthropic exhibits the clearest positive release profile through Claude Code and product-model fit, OpenAI shows backlash-and-recovery dynamics around GPT-5 and GPT-5.1, Grok-3 is shaped by provider identity and political discourse, and DeepSeek-R1 combines engineering praise with concerns about censorship, access, and reliability. These findings show that model releases are not merely technical updates, but user-facing interventions that reshape sentiment, expectations, and public discussion.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 5 of its 31 references that are in the map. First posted on arXiv 25 Aug 2026.

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5 of 31 references.

References · 5

  1. 2024AnthroScore: A Computational Linguistic Measure of Anthropomorphismcited by 27
  2. 2023Public Attitudes Toward ChatGPT on Twitter: Sentiments, Topics, and Occupationscited by 6
  3. 2026"Please, don't kill the only model that still feels human": Understanding the #Keep4o Backlashcited by 5
  4. 2026Bowling with ChatGPT: On the Evolving User Interactions with Conversational AI Systemscited by 4
  5. 2025Winning and losing with Artificial Intelligence: What public discourse about ChatGPT tells us about how societies make sense of technological changecited by 1

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  1. 2026How Far Did They Go? The Persuasive Tactics of Covert LLM Agents in a Discontinued Field Experiment
  2. 2026Comparing Sentiment Contagion in AI-Agent and Human Social Networks: Evidence from MOLTBOOK
  3. 2026ExpressionCueLens: A Cross-Cultural Analysis of Human-AI Companion Conversations on Social Media ↗
  4. 2026Modeling Community Attitude through Reaction Tone: A Human-AI Collaborative Framework for Evaluating LLM Alignment with Linguistic Behaviors in Online Communities
  5. 2026Evaluating the Realism of LLM-powered Social Agents: A Case Study of Reactions to Spanish Online News
  6. 2025Who's Sorry Now: User Preferences Among Rote, Empathic, and Explanatory Apologies from LLM Chatbots
  7. 2025RedditESS: A Mental Health Social Support Interaction Dataset -- Understanding Effective Social Support to Refine AI-Driven Support Tools
  8. 2022"I think this is the most disruptive technology": Exploring Sentiments of ChatGPT Early Adopters using Twitter Data