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User reviews published in mobile app repositories are essential forunderstanding user satisfaction and engagement within a specific marketsegment. Manual analysis of these reviews is impractical due to the largevolume of available data, while automatic analysis poses several challenges,including data synthesis and effective reporting. These challenges complicatethe task for app providers in identifying hidden patterns and significantevents related to app acceptance, especially in assessing the influence ofcompetitor apps. Furthermore, review-based analysis is mostly limited to asingle app or a single app provider, excluding potential market and competitionanalysis. Following a case-study research method in the microblogging appmarket, we introduce an automatic, novel approach to support mobile app marketanalysis processes through quantitative metrics and event detection techniquesbased on newly published user reviews. Significant events are proactivelyidentified and summarized by comparing metric deviations with historicalbaseline indicators within the lifecycle of a mobile app. Results from our casestudy show empirical evidence of the detection of relevant events within theselected market segment, including software- or release-based events,contextual events and the emergence of new competitors.

Unveiling Competition Dynamics in Mobile App Markets through User Reviews