Modeling Co-Engagement Patterns in Brand Information Networks

Pankhuri Malhotra, Yaxin Cui, Keran Zhao

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

Abstract

The rise in electronic interactions has made information networks ubiquitous. Correspondingly, research across multiple domains has begun to explore the social and economic value of information networks for business decision-making. While most existing research focuses on descriptive and predictive properties of information networks, statistical analysis of the 'generative features' of information networks has largely been overlooked. The objective of our study is to create large-scale brand information networks, from common followership data on Twitter, and to model the generative features of the observed network structures. We propose to employ Exponential Random Graph Models to reveal a mix of network and individual level brand characteristics responsible for the formation of links between brands. Since links between brands arise from the aggregated interest patterns of Twitter users, the ERGM model essentially reveals brand and network characteristics associated with high user co-engagement patterns on social media.

Original languageEnglish (US)
Title of host publicationProceedings - 16th IEEE International Conference on Semantic Computing, ICSC 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages257-262
Number of pages6
ISBN (Electronic)9781665434188
DOIs
StatePublished - 2022
Event16th IEEE International Conference on Semantic Computing, ICSC 2022 - Virtual, Online, United States
Duration: Jan 26 2022Jan 28 2022

Publication series

NameProceedings - 16th IEEE International Conference on Semantic Computing, ICSC 2022

Conference

Conference16th IEEE International Conference on Semantic Computing, ICSC 2022
Country/TerritoryUnited States
CityVirtual, Online
Period1/26/221/28/22

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computer Networks and Communications
  • Computer Science Applications
  • Information Systems and Management

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