Applying Modality and Equivalence Concepts to Pattern-Finding in Social Process-Produced Data (2011)
by Robert A. Hanneman and Christian R. Shelton
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.
Download Information
Robert A. Hanneman and Christian R. Shelton (2011). "Applying Modality and Equivalence Concepts to Pattern-Finding in Social Process-Produced Data." Social Network Analysis and Mining, 1, 59-72.
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Bibtex citation
@article{HanShe11,
author = "Robert A. Hanneman and Christian R. Shelton",
title = "Applying Modality and Equivalence Concepts to Pattern-Finding in Social Process-Produced Data",
journal = "Social Network Analysis and Mining",
journalabbr = "SNAM",
year = 2011,
volume = 1,
pages = "59--72",
}