Network structure shapes consensus dynamics through individual decisions

Area of Science:

• Social Psychology
• Computational Social Science
• Network Science

Background:

• Network structure influences group consensus in simplified tasks.
• Cognitive mechanisms linking network structure to narrative emergence are unclear.
• Decentralized online networks present complex environments for studying shared narratives.

Purpose of the Study:

• To investigate how network structure affects the emergence and semantic content of shared narrative beliefs.
• To explore the cognitive mechanisms underlying narrative formation in online social networks.
• To analyze the impact of network topology on causal and effect-focused communication.

Main Methods:

• Experimental online social networks were utilized.
• Natural language processing (NLP) measures and agent-based modeling were employed.
• An embedding-based narrative alignment measure quantified semantic similarity.

Main Results:

• Complex media content attenuated network structure effects but did not eliminate them.
• Fully connected networks prioritized communicating causes, while locally connected networks emphasized effects.
• Network structure influenced representational and language change, with fully connected groups increasing causal language.

Conclusions:

• Network structure significantly shapes the semantic content and linguistic features of shared narratives.
• Online social network topology influences whether groups focus on causes or effects.
• Findings highlight the interplay between network architecture and cognitive processes in collective sense-making.