The Role of Arousal and Valence in Predictions of Short Video Virality: A Psychophysiological Perspective

Computers in Human Behavior. 2026. Vol. 184. Article 109060.

Shelepenkov D., Kosonogov V.

In the current digital age, content sharing is widespread, especially on social platforms. Our research explores the intricate relationship between neurophysiological mechanisms, emotions, and information sharing. We involved 28 regular TikTok users, assessing their inclination to share short videos. Alongside participant preferences, we recorded electroencephalographic (EEG) activity and peripheral signals (heart rate, facial muscle activity, and skin conductance) for all the content, along with sharing ratings and likes. Our research has shown that content causing greater arousal and positive emotions is more likely to be shared. Moreover, measurements of a small group of people can predict the behavior of social network users in general. Thus, physiologically associated measures with emotional reactions showed correlated with both sharing decisions of our participants and with global TikTok sharing and likes metrics. We show that the combination of physiological measures and EEG signals from a small group of subjects can have high explanatory power for content distribution (R2 = 0.51) in the general population and outperform models based only on physiological measures by 39%.

Keywords: EEG, social media, prediction, virality, ECG

Publication based on the results of: Mental health research: behavioral and neurophysiological foundations (2025)