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Applying modality and equivalence concepts to pattern finding in social process-produced data

Authors
  • Hanneman, Robert A.1
  • Shelton, Christian R.2
  • 1 University of California, Department of Sociology, Riverside, USA , Riverside (United States)
  • 2 University of California, Department of Computer Science and Engineering, Riverside, USA , Riverside (United States)
Type
Published Article
Journal
Social Network Analysis and Mining
Publisher
Springer Vienna
Publication Date
Oct 05, 2010
Volume
1
Issue
1
Pages
59–72
Identifiers
DOI: 10.1007/s13278-010-0009-1
Source
Springer Nature
Keywords
License
Green

Abstract

Large amounts of detailed transactional information are generated by ongoing social processes. For managing and mining such data, we treat them as “objects” and “relations”. These ideas strongly parallel the way that social network analysts conceive of social structure. Modality (roughly, distinguishing multiple classes of social actors or nodes in networks) and equivalence classes (roughly, distinguishing general patterns in the ways that objects in classes are related to one another or to objects in other classes) have proven to be very useful in helping social network analysts to think about complex relational structures among social objects. Dimensional and generalized “block models” of multi-modal social networks provide tools for designing searches to identify patterns. The ideas are illustrated by descriptions of how a number of social process-produced data might be approached, including bibliographic databases, communications logs, virtual communities, and economic transactions.

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