Keywords
Spillovers, user reviews, word-of-mouth, emotions, artificial intelligence
Paper Type
Complete
Abstract
Major model releases of AI platforms via version updates have become market-wide events that can reset expectations and shift how users compare competing platforms. However, there is little understanding of how competitive spillovers occur in such platforms. We examine whether these releases and updates affect how rivals are evaluated by analyzing 1,287,865 Google Play reviews for ChatGPT, Gemini, DeepSeek, and Grok, covering 288 app versions from February 2023 to September 2025. We align review timestamps with app version histories and platform-level model releases to examine whether one platform’s releases coincide with shifts in rivals’ review discourse. We found that major releases are followed by changes in the emotional tone of how rivals are evaluated, in addition to shifts in the themes users emphasize in their reviews. Overall, our findings suggest that emotional tone in app reviews provides a useful way to observe event-driven competitive spillovers in AI platform markets.
Recommended Citation
Manikonda, Lydia; Hämäläinen, Antti; Rochholz, David; and Gräf, Miriam, "Competitive Spillovers from AI Version Updates: Evidence from AI Platform App Reviews" (2025). ICIS 2025 Proceedings. 1.
https://aisel.aisnet.org/icis2025/paperathon/paperathon/1
Competitive Spillovers from AI Version Updates: Evidence from AI Platform App Reviews
Major model releases of AI platforms via version updates have become market-wide events that can reset expectations and shift how users compare competing platforms. However, there is little understanding of how competitive spillovers occur in such platforms. We examine whether these releases and updates affect how rivals are evaluated by analyzing 1,287,865 Google Play reviews for ChatGPT, Gemini, DeepSeek, and Grok, covering 288 app versions from February 2023 to September 2025. We align review timestamps with app version histories and platform-level model releases to examine whether one platform’s releases coincide with shifts in rivals’ review discourse. We found that major releases are followed by changes in the emotional tone of how rivals are evaluated, in addition to shifts in the themes users emphasize in their reviews. Overall, our findings suggest that emotional tone in app reviews provides a useful way to observe event-driven competitive spillovers in AI platform markets.
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