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Inferring a Mobile User’s Valence and Arousal through On-Screen Text AnalysisEdita Džubur,
Veljko Pejović, 2025, independent scientific component part or a chapter in a monograph
Abstract: Understanding a user’s emotional state is critical for building adaptive and intelligent mobile applications. In this paper we investigate the feasibility of inferring valence and arousal from the text displayed on smartphone screens. We developed AV-Sense, a mobile application that combines the Experience Sampling Method, a technique that prompts users to report their feelings in the moment, with passive screentext logging. In a two-week study with 12 participants, we collected 787 ESM responses and over 650,000 screentext entries. Data analysis revealed meaningful temporal and individual patterns in reported affect. We then explored the use of large language models to predict valence and arousal from screentext, but results indicated limited predictive power in this setting. Our findings highlight both the potential and current challenges of screentext-based affect inference, laying the groundwork for future research on emotion-aware applications and naturalistic psychological studies.
Keywords: text analysis, experience sampling method, screentext sensing, valence, arousal, large language models
Published in RUP: 30.01.2026; Views: 950; Downloads: 4
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