Through decades of research, scholars have illustrated the complexity of the relationship between unobservable personalities and observable behaviors. Yet, despite this complexity, the predominant empirical method of assessing personality remains the psychometric scale. In this dissertation, I extend past research on behavioral measures of personality by proposing a novel approach using natural language, and highlight at least three key ways it helps advance our understanding of personality and behavior. First, assessing personality from behavior directly bypasses potential cognitive and perceptual biases involved in the self- and peer-report of scales, allowing for a more objective account. Second, it uncovers temporal and situational variance largely obscured by scales, which capture mean tendencies and more stable, individual differences. Third, it has greater potential to shed light on the processes underlying documented correlations between personality and distal outcomes.

In Chapter 1, I review the personality and behavior literature and draw out two major conclusions, describing how they have led to three different methods of personality assessment. I discuss the limitations of these methods, explain how my approach overcomes these limitations, and introduce the personality construct of self-monitoring through which I illustrate my approach. In Chapter 2, I detail the construction of a behavioral measure of self-monitoring. I explain how characteristics of the technical apparatus map on to the general theory of self-monitoring, outline the design decisions I made in constructing the measure, and provide comparisons with the survey measure as well as robustness checks. In Chapter 3, I conclude with an empirical analysis of the measure, demonstrating that it is responsive to situations as expected. I additionally demonstrate its utility in its association with consequential individual outcomes such as salary bonus and network constraint.

This dissertation examines how people express and exchange emotions in the workplace and how these expressions relate to their social positions in organizational networks. Prior literature has tended to focus on employees’ expressed emotions towards external actors, such as customers, which are often required by their job roles; this dissertation instead focuses on emotional exchanges between colleagues in routine communications at work. I investigate four key questions: (1) How do people express emotions in the workplace? (2) How do people respond to the emotions of others in the workplace? (3) What kinds of emotional expressions are associated with valuable positions in organizational networks, and for whom? (4) Are there social network rewards (or penalties) associated with engaging in the emotion work of aligning towards colleagues’ emotions? Core to this inquiry is gender, as a primary cultural frame for organizing social relations. I bridge insights from the sociology of gender with the social psychology of emotion to unpack how these factors shapes people’s tendencies to express their emotions, respond to the emotions of their colleagues, and construct and navigate networks inside of organizations.

Findings from these studies contribute to research across five domains by: (1) enhancing our understanding of the cultural and emotional experience of employees in the workplace; (2) unearthing a less visible form of emotion work; (3) highlighting gender differences in emotional expressions, emotion work, and social network positions; (4) expanding interactional accounts of how individuals navigate social networks; and (5) identifying gendered and emotional correlates of social network positions.