Time-dependent association between mass protests and psychological distress on social media: A text mining study during the 2019 anti-government social unrest in Hong Kong

Abstract

Background & aims: Social media are increasingly pivotal as the platform where activists and observers plan, promote, and respond to collective actions. To examine how mass protests influence psychological wellbeing and distress, this study analyzed their time-dependent association during the 2019 anti-government social unrest in Hong Kong.

Methods: Consecutive day-by-day users-generated content on online forums and social network sites (SNS) from June to November 2019 was obtained. A Cantonese term-list was created to identify terms related to mass protests and psychological distress. The frequency of comments containing such terms was analyzed using time series models.

Results: There were 3,572,665 social media comments in the investigation period. As hypothesized, the frequency of comments with mass protest terms was higher on days with mass protests than on days without. Frequency of comments with both mass protest- and psychological distress-terms was also higher on days with protests than days without. Time-lagged effect (responses on the following day) of protest-terms was found on online forums but not on SNS. Our results suggest a positive association between offline protest activities and online psychological reactions.

Conclusions: Social media content reveals discussions of psychological distress stemming from, or exacerbated by, social unrest. The potential mutual influences between mass protests and online reactions, as well as the functional differences between online forums and SNS in this regard are discussed. Street protests and their associated psychological distress can be readily detected on popular online forums. Mental health services should consider, and even make use of, such dynamic relationship between on- and offline activities.