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.
Highlights
Hundreds of papers in psychology, medicine, marketing, management, and many other fields begin by asserting that emotions are ubiquitous to human life
In terms of mixed emotions, the emotions that most frequently co-occurred with an opposite valence emotion were anxiety and love
Our findings revealed that everyday human life is profoundly emotional: people reported experiencing at least one emotion 90% of the time
Summary
Hundreds of papers in psychology, medicine, marketing, management, and many other fields begin by asserting that emotions are ubiquitous to human life. A tremendous body of work has established that various stimuli and situations can cause emotions [1,2,3,4] and that once people experience emotions, it guides their thoughts and behaviors [5, 6]. Answering these fundamental questions about the frequency and centrality (i.e., interconnectedness) of emotions in everyday life is crucial to our understanding of human experience and may guide research and interventions in important ways. We report the first “big data” account of how people experience emotions in real-time in their everyday life. Bringing together network science and emotion research for the first time, we use network analysis to elucidate interrelations between emotions. This approach provides new insights into our everyday emotional life
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