Tim Verbeij, Ine Beyens, Damian Trilling, Patti M. Valkenburg
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引用次数: 0
Abstract
We investigated the expressions of happiness and sadness in adolescents’ direct messages (DMs) on Instagram. Using neural topic modeling ( BERTopic), we analyzed 211,778 DMs belonging to 96 adolescents, who donated data from 101 Instagram accounts. Results showed that (1) expressions of happiness were more than four times more prevalent than expressions of sadness; (2) the number of DMs containing expressions of happiness and expressions of sadness were highly correlated; (3) there are temporal trends in the expression of happiness and sadness in adolescents’ DMs, and there are individual differences in these trends; and (4) there is no significant between- or within-person relationship between the number of DMs containing expressions of happiness and sadness and adolescents’ well-being.
期刊介绍：
Social Media + Society is an open access, peer-reviewed scholarly journal that focuses on the socio-cultural, political, psychological, historical, economic, legal and policy dimensions of social media in societies past, contemporary and future. We publish interdisciplinary work that draws from the social sciences, humanities and computational social sciences, reaches out to the arts and natural sciences, and we endorse mixed methods and methodologies. The journal is open to a diversity of theoretic paradigms and methodologies. The editorial vision of Social Media + Society draws inspiration from research on social media to outline a field of study poised to reflexively grow as social technologies evolve. We foster the open access of sharing of research on the social properties of media, as they manifest themselves through the uses people make of networked platforms past and present, digital and non. The journal presents a collaborative, open, and shared space, dedicated exclusively to the study of social media and their implications for societies. It facilitates state-of-the-art research on cutting-edge trends and allows scholars to focus and track trends specific to this field of study.
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