The Moral Structure of Identities: A Bipartite Network Approach

• In Event: Student Forum Roundtables Session
  In Refereed Roundtable (90 minute): Roundtable 20: Sociological Theory and Methods

Abstract

Identity theory posits that identities are sets of meanings, yet most empirical work measures identity meanings using dimensional summaries that discard semantic content or study identities one at a time, often ignoring how these identities might be interconnected. This study uses a bipartite network analysis approach to map the associative connections between identities and specific traits. I argue that some identities carry contradictory moral meanings, such as "soldier" connecting to traits such as "brave" and "violent", and that this structural moral ambiguity is ignored by standard affect control theory profiles. Using survey data, I construct a bipartite network of approximately 80 identities and 50 traits and operationalize moral ambiguity as bridging between positive and negative meaning clusters. I argue that identities containing both affectively positive and affectively negative trait associations can result in recurrent identity nonverification as it becomes increasingly difficult to verify the moral content of one's identity as moral ambiguity increases. This bipartite network approach can help reveal which specific meanings are in conflict and how those meanings are organized across identity structures. This information is necessary for understanding how cultural associations can affect the identity verification process by providing potentially conflicting affective meanings.

Author

• Daniel Reich, Duke University