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Poster A37 in Poster Session A - Tuesday, August 6, 2024, 4:15 – 6:15 pm, Johnson Ice Rink
How does shared reality generalize?
Wasita Mahaphanit1 (), Christopher Welker1, Helen Schmidt2, Luke Chang1, Robert Hawkins3; 1Dartmouth College, 2Temple University, 3University of Wisconsin-Madison
We use a Bayesian inductive reasoning model to test whether generalized shared reality (i.e., the sense of being on the same page) arises through probabilistic inference about latent commonalities. Using a naturalistic text-based chat paradigm, we manipulated whether conversation partners were assigned to discuss a belief they shared, a belief on which their opinions differed, or a random prompt. Subsequently, we asked participants to predict their conversation partner's beliefs and opinions on topics that were not assigned for discussion. We show that an inferential model that incorporates knowledge of the identified commonality from the chat phase captures participants' expectations of shared opinions with their chat partner. Our findings suggest that participants leverage the alignment of their opinions and the topic they share opinions on -- a singular instance of shared experience -- to infer other latent shared commonalities with their conversation partners, thereby generalizing to a broader shared reality. This work lays the foundation for a mechanistic understanding of generalized shared reality and its role in fostering a sense of connection between conversation partners.
Keywords: social cognition shared reality bayesian probabilistic