A multi-theoretical framework for hypotheses testing of temporal network patterns

Shan Jiang, Hsinchun Chen

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Online social networks are multi-dimensional and dynamic. By combining these two perspectives, we can differentiate between various temporal patterns, better understand the mechanisms behind network formation, and test theories that are potentially associated with the behaviors of individuals online. In this study, we develop a temporal network analysis model and a multi-theoretical framework for examining various temporal network patterns in multi-dimensional networks. The proposed framework suggests a list of temporal patterns that may be observed in online social networks, including temporal reciprocity, co-occurrence, triangle, and k-star. We also provide theoretical explanations for why these patterns could be observed. This study provides a generalized framework to explore, analyze, and explain various temporal patterns in online social networks. An empirical test of our framework in the context of online social communities is outlined. The extended multi-theoretical framework can be easily applied to any social network that shows multi-dimensionality.

Original languageEnglish (US)
Title of host publication35th International Conference on Information Systems "Building a Better World Through Information Systems", ICIS 2014
PublisherAssociation for Information Systems
ISBN (Print)9781634396943
StatePublished - 2014
Event35th International Conference on Information Systems: Building a Better World Through Information Systems, ICIS 2014 - Auckland, New Zealand
Duration: Dec 14 2014Dec 17 2014

Other

Other35th International Conference on Information Systems: Building a Better World Through Information Systems, ICIS 2014
Country/TerritoryNew Zealand
CityAuckland
Period12/14/1412/17/14

Keywords

  • Exponential random graph models
  • Social media
  • Social network

ASJC Scopus subject areas

  • Information Systems
  • Computer Science Applications

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