Social distance and network structures

This paper analyzes how agents' perception of relationships with others determines the structures of networks. In our model, agents are endowed with their own multi-dimensional characteristics and form links depending on the social distance between them. We characterize average path length and clustering coefficient in stable networks, and analyze how they are related to the way social distances are measured by agents. One implication is that the introduction of new communication technology makes a network closely connected but not cliquish. We relate our model and results to Granovetter's ``strength of weak ties hypothesis," Tversky's ``similarity scale," and Mobius-Rosenblat's ``communication externality."

• Publication year

  2017

• Venue

  Theoretical Economics

• Publication date

  2017-05-01

• Fields of study

  Sociology, Computer Science, Mathematics

• Identifiers
  DOI 10.3982/TE1873
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

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