Networks Evolving Step by Step: Statistical Analysis of Dyadic Event Data

With few exceptions, statistical analysis of social networks is currently focused on cross-sectional or panel data. On the other hand, automated collection of network-data often produces event data, i.e., data encoding the exact time of interaction between social actors. In this paper we propose mod...

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Bibliographic Details
Published in2009 International Conference on Advances in Social Network Analysis and Mining : 20-22 July 2009 pp. 200 - 205
Main Authors Brandes, U., Lerner, J., Snijders, T.A.B.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.07.2009
Subjects
Computer networks
Design methodology
Encoding
event data
Frequency
Information analysis
Information science
longitudinal analysis
political networks
signed networks
Social network services
social networks
Statistical analysis
Statistics
structural balance theory
Testing
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ISBN9780769536897
0769536891
DOI10.1109/ASONAM.2009.28

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Summary:With few exceptions, statistical analysis of social networks is currently focused on cross-sectional or panel data. On the other hand, automated collection of network-data often produces event data, i.e., data encoding the exact time of interaction between social actors. In this paper we propose models and methods to analyze such networks of dyadic events and to determine the factors that influence the frequency and quality of interaction. We apply our methods to empirical datasets about political conflicts and test several hypotheses concerning reciprocity and structural balance theory.
ISBN:9780769536897
0769536891
DOI:10.1109/ASONAM.2009.28