On the causal relation between real world activities and emotional expressions of social media users

• Published in: Journal of the American Society for Information Science and Technology 2021-06, Vol.72 (6), p.723-743
• Main Authors: Mirlohi Falavarjani, Seyed Amin, Jovanovic, Jelena, Fani, Hossein, Ghorbani, Ali A., Noorian, Zeinab, Bagheri, Ebrahim
• Format: Article
• Language: English
• Subjects: Design of experiments; Digital media; Emotions; Human-computer interaction; Moods; Recommender systems; Research design; Social factors; Social media; Social networks
• ISSN: 2330-1635; 2330-1643
• DOI: 10.1002/asi.24440

Social interactions through online social media have become a daily routine of many, and the number of those whose real world (offline) and online lives have become intertwined is continuously growing. As such, the interplay of individuals' online and offline activities has been the subject of numerous research studies, the majority of which explored the impact of people's online actions on their offline activities. The opposite direction of impact—the effect of real‐world activities on online actions—has also received attention but to a lesser degree. To contribute to the latter form of impact, this paper reports on a quasi‐experimental design study that examined the presence of causal relations between real‐world activities of online social media users and their online emotional expressions. To this end, we have collected a large dataset (over 17K users) from Twitter and Foursquare, and systematically aligned user content on the two social media platforms. Users' Foursquare check‐ins provided information about their offline activities, whereas the users' expressions of emotions and moods were derived from their Twitter posts. Since our study was based on a quasi‐experimental design, to minimize the impact of covariates, we applied an innovative model of computing propensity scores. Our main findings can be summarized as follows: (a) users' offline activities do impact their affective expressions, both of emotions and moods, as evidenced in their online shared textual content; (b) the impact depends on the type of offline activity and if the user embarks on or abandons the activity. Our findings can be used to devise a personalized recommendation mechanism to help people better manage their online emotional expressions.