Openness to Experience and Semantic Network Reorganization
Restricted (Penn State Only)
- Author:
- Zeitlen, Daniel
- Graduate Program:
- Psychology (MS)
- Degree:
- Master of Science
- Document Type:
- Master Thesis
- Date of Defense:
- August 19, 2022
- Committee Members:
- Roger Beaty, Thesis Advisor/Co-Advisor
Janet Van Hell, Committee Member
Kristin Buss (She/Her), Program Head/Chair
Chaleece Sandberg (She/Her), Committee Member - Keywords:
- semantic memory
openness to experience
conceptual combination - Abstract:
- Semantic memory has been increasingly studied using semantic network analysis, which models semantic memory structure (i.e., the organization of how concepts are related within semantic memory) as a network. While semantic memory is a dynamic cognitive system, few semantic network studies have assessed how semantic network structure can change with experience—a process central to learning new information. In the present study, we aimed to replicate the findings of a recent foundational study on semantic network reorganization—that a relational, but not attributive, conceptual combination task intervention resulted in reorganization of semantic networks, such that the flexibility and efficiency of the network structure was increased. We also examined how openness to experience, a personality trait linked to flexible thinking and semantic network structure, may impact semantic network reorganization. We followed the procedure of the original study and measured semantic memory using a free association task at two time points, before and after participants completed either a relational intervention (N = 114), an attributive intervention (N = 117), or no intervention in the baseline condition (N = 129). Semantic networks were modeled for each group (pre- and post-intervention), and we applied a bootstrapping method with 1,000 iterations to test differences in network structure between semantic networks. The present study replicated the semantic network reorganization results following the attributive intervention, but not in the relational or baseline conditions (which exhibited unexpected patterns of reorganization). Furthermore, we reran the semantic network analyses after subdividing conditions into high and low openness groups, and found that openness influenced the degree (but not pattern) of semantic network reorganization across conditions, with lower openness linked to greater reorganization. Altogether, the findings provide novel evidence on semantic network reorganization, including the first direct evidence linking changes in semantic network structure to an individual trait, and support the view that semantic memory structure is a dynamic and updating system.