Julia Moeller

Mixed Emotions: Network Analyses of Intra-Individual Co-occurrences Within and Across Situations

This study revisits the structure of emotions by using a co-occurrence network analysis. While previous studies have examined the structure of emotions primarily through interindividual correlations, we investigated how often and which specific positive and negative emotions occur together within individuals. Two studies were conducted with high school students, one (N = 21,678) using retrospective emotion measures (open-ended questions and 28 rated items) and the other (N = 472) using in-the-moment emotion measures (experience sampling). As in previous studies, positive and negative emotion ratings were negatively correlated across individuals, and this negative correlation became stronger when measurement error was controlled. Nevertheless, network analyses of both the open-ended responses and of emotion rating scales found frequent co-occurrences between both positive and negative emotions within individuals and within situations. Across all networks, happy, tired, and stressed were among the most frequent emotions that occurred together with emotions of opposite valence. The network analyses presented in this article open new directions to the long-lasting debate about the structure of emotions by revealing co-occurrences that interindividual correlations would not show.

Passion and Motivation

This article gives an overview about a decade of passion research (2003–2013). First, definitions and measurements of passion are introduced, differentiating between general models on the one hand and domain-specific definitions on the other hand. Second, the relations of passion to other constructs are addressed and the research findings concerning similar constructs, predictors, correlates, and outcomes of passion are summarized. Finally, open research questions and directions for future research are discussed.

Gender Identity and Sexual Identity Labels Used by U.S. High School Students: A Co-occurrence Network Analysis.

In a survey of 19,385 U.S. high school students, we investigated which labels students used to describe their gender and sexual identities, and which of these labels were mentioned together. The survey offered five predefined categories for gender identity (male, female, trans male, trans female, or “different”), and four categories for sexual identity (heterosexual/straight, lesbian/gay, bisexual, or “other”). Adolescents were invited to provide their own labels if the offered categories did not adequately describe their identity. Most participants who opted to use the open-ended fields provided a single label, but some provided up to four. All open-ended responses were counted and subjected to a co-occurrence network analysis, where co-occurrence was defined as two labels being mentioned together by the same student. Analysis identified two distinct subnetworks or clusters: the first included primarily predefined traditional labels of gender identity and sexual identity, and the second included student-generated labels reported in the open-ended response fields, indicating that “different” gender identities and “other” sexual identities are often mentioned together. The use and implications of these labels are discussed.