Identifying influential users in social media:A study of U.S. Immigration reform

Wingyan Chung, Daniel Zeng, Nathan O'Hanlon

Research output: Contribution to conferencePaperpeer-review

3 Scopus citations


As opinion leaders and key participants emerge in social media, identifying influential users can help decision makers to effectively target the source of influence and hence bring about change in the communities. In this research, we developed an approach to identifying influential users in online social networks of interest to policy makers and the general public. We present findings from an empirical study of the U.S. immigration reform discussion, in which more than 300, 000 users posted 909, 035 tweets during May-November 2013. We present findings of our analysis, provide the lists of influential users identified, and discuss the implication on predictive analytics and social media analytics. This research should contribute to providing a new case and new empirical findings of applying influence analytics to analyzing social media networks, and has strong implications on predictive analytics, business intelligence, and social media analytics.

Original languageEnglish (US)
StatePublished - Jan 1 2014
Event20th Americas Conference on Information Systems, AMCIS 2014 - Savannah, GA, United States
Duration: Aug 7 2014Aug 9 2014


Other20th Americas Conference on Information Systems, AMCIS 2014
Country/TerritoryUnited States
CitySavannah, GA


  • Business intelligence
  • Influence
  • Influential users
  • Predictive analytics
  • Social media analytics
  • Social network analysis
  • Text mining
  • U.S. Immigration reform

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Computer Science Applications
  • Information Systems
  • Library and Information Sciences


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