Dataset Information

Emotions in Everyday Life.

ABSTRACT: Despite decades of research establishing the causes and consequences of emotions in the laboratory, we know surprisingly little about emotions in everyday life. We developed a smartphone application that monitored real-time emotions of an exceptionally large (N = 11,000+) and heterogeneous participants sample. People's everyday life seems profoundly emotional: participants experienced at least one emotion 90% of the time. The most frequent emotion was joy, followed by love and anxiety. People experienced positive emotions 2.5 times more often than negative emotions, but also experienced positive and negative emotions simultaneously relatively frequently. We also characterized the interconnections between people's emotions using network analysis. This novel approach to emotion research suggests that specific emotions can fall into the following categories 1) connector emotions (e.g., joy), which stimulate same valence emotions while inhibiting opposite valence emotions, 2) provincial emotions (e.g., gratitude), which stimulate same valence emotions only, or 3) distal emotions (e.g., embarrassment), which have little interaction with other emotions and are typically experienced in isolation. Providing both basic foundations and novel tools to the study of emotions in everyday life, these findings demonstrate that emotions are ubiquitous to life and can exist together and distinctly, which has important implications for both emotional interventions and theory.

SUBMITTER: Trampe D

PROVIDER: S-EPMC4689475 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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Emotions in Everyday Life.

Trampe Debra D Quoidbach Jordi J Taquet Maxime M

PloS one 20151223 12

Despite decades of research establishing the causes and consequences of emotions in the laboratory, we know surprisingly little about emotions in everyday life. We developed a smartphone application that monitored real-time emotions of an exceptionally large (N = 11,000+) and heterogeneous participants sample. People's everyday life seems profoundly emotional: participants experienced at least one emotion 90% of the time. The most frequent emotion was joy, followed by love and anxiety. People ex ...[more]

PMID: 26698124

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Project description:BACKGROUND: E-communities, social groups interacting online, have recently become an object of interdisciplinary research. As with face-to-face meetings, Internet exchanges may not only include factual information but also emotional information--how participants feel about the subject discussed or other group members. Emotions in turn are known to be important in affecting interaction partners in offline communication in many ways. Could emotions in Internet exchanges affect others and systematically influence quantitative and qualitative aspects of the trajectory of e-communities? The development of automatic sentiment analysis has made large scale emotion detection and analysis possible using text messages collected from the web. However, it is not clear if emotions in e-communities primarily derive from individual group members' personalities or if they result from intra-group interactions, and whether they influence group activities. METHODOLOGY/PRINCIPAL FINDINGS: Here, for the first time, we show the collective character of affective phenomena on a large scale as observed in four million posts downloaded from Blogs, Digg and BBC forums. To test whether the emotions of a community member may influence the emotions of others, posts were grouped into clusters of messages with similar emotional valences. The frequency of long clusters was much higher than it would be if emotions occurred at random. Distributions for cluster lengths can be explained by preferential processes because conditional probabilities for consecutive messages grow as a power law with cluster length. For BBC forum threads, average discussion lengths were higher for larger values of absolute average emotional valence in the first ten comments and the average amount of emotion in messages fell during discussions. CONCLUSIONS/SIGNIFICANCE: Overall, our results prove that collective emotional states can be created and modulated via Internet communication and that emotional expressiveness is the fuel that sustains some e-communities.

Dataset Information

Emotions in Everyday Life.

Publications

Emotions in Everyday Life.

Similar Datasets

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