A social network is a set of actors (e.g., person, team, firm) and the ties connecting them (e.g., relationship, exchange, or interaction). These ties serve as conduits through which resources such as information flow; they also serve as prisms through which to make inferences and shape perceptions. Social network analysis (SNA) is the use of graph-theoretic and matrix algebraic techniques to study the social structure and strategic positions of actors in social networks. As a methodological tool, SNA allows scholars to visualize and analyze webs of ties to identify their origins and dynamics and link these structures to actors’ attitudes and behaviors. In this session, we will discuss (1) how to define the boundaries of a social network, (2) approaches (and challenges) to collecting network data, (3) metrics that can be derived from network data, (4) linking network data and theory, and (5) research questions to which social network analysis can be applied. A major appeal of network analysis is the distinctive lens it offers to examine a range of organizational phenomena at different levels; so, this session may be of interest to scholars studying topics such as trust, leadership, human capital, mentoring, DE&I, groups and teams, communication, work-nonwork interface, newcomer socialization, emotions, and employee well-being.