Proceedings of the International AAAI Conference on Web and Social Media · 2021 · 165 citations · 23 references
Social SciencesCommunicationSocial PsychologyInterpersonal CommunicationSocial Media AnalyticsSociolinguisticsAffective CommunicationAffective ComputingEmotion RecognitionMoodOpinion MiningSocial MediaConversational EngagementEmotion DetectionSocial Media CorporaText-based Emotion AnalysisValence Modeling
Emotional states shape expression, attitudes, and behavior, and as social media becomes a primary channel for daily updates, mapping these moods is essential for interpreting large-scale online behavior. The study investigates the circumplex model of affect, which represents mood through valence and activation dimensions, to map human emotional states on Twitter. Using Mechanical Turk and literature sources, the authors identified over 200 Twitter moods and examined their relationships with linguistic diversity, social ties, network activity, and engagement behaviors. The results provide large‑scale, naturalistic validation and extensions of existing mood conceptualizations in social media contexts.
Emotional states of individuals, also known as moods, are central to the expression of thoughts, ideas and opinions, and in turn impact attitudes and behavior. As social media tools are increasingly used by individuals to broadcast their day-to-day happenings, or to report on an external event of interest, understanding the rich ‘landscape’ of moods will help us better interpret and make sense of the behavior of millions of individuals. Motivated by literature in psychology, we study a popular representation of human mood landscape, known as the ‘circumplex model’ that characterizes affective experience through two dimensions: valence and activation. We identify more than 200 moods frequent on Twitter, through mechanical turk studies and psychology literature sources, and report on four aspects of mood expression: the relationship between (1) moods and usage levels, including linguistic diversity of shared content (2) moods and the social ties individuals form, (3) moods and amount of network activity of individuals, and (4) moods and participatory patterns of individuals such as link sharing and conversational engagement. Our results provide at-scale naturalistic assessments and extensions of existing conceptualizations of human mood in social media contexts.
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James A. Russell · Journal of Personality and Social Psychology · 1980 · 16K citations
Anxiety and the Anxiety Disorders
A. H. Tuma, Jack D. Maser · International Clinical Psychopharmacology · 1990 · 1.3K citations
Education, Psychiatry, Psychology +12