
TL;DR
This paper discusses methods for simplifying large social networks by identifying actor roles, which helps in understanding network structure and predicting behavior.
Contribution
It introduces a role classification approach for social network actors, aiding in network summarization and analysis.
Findings
Role classification enhances understanding of network organization
Simplified networks retain key communication patterns
Method supports behavior prediction in social networks
Abstract
A social network consists of a set of actors and a set of relationships between them which describe certain patterns of communication. Most current networks are huge and difficult to analyze and visualize. One of the methods frequently used is to extract the most important features, namely to create a certain abstraction, that is the transformation of a large network to a much smaller one, so the latter is a useful summary of the original one, still keeping the most important characteristics. In the case of a social network it can be achieved in two ways. One is to find groups of actors and present only them and relationships between them. The other is to find actors who play similar roles and to construct a smaller network in which the connection between the actors would be replaced with connections between the roles. Classifying actors by the roles they are playing in the network can…
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