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

Wingyan Chung, Dajun Zeng, Nathan O'Hanlon

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

3 Citations (Scopus)

Abstract

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)
Title of host publication20th Americas Conference on Information Systems, AMCIS 2014
PublisherAssociation for Information Systems
StatePublished - 2014
Event20th Americas Conference on Information Systems, AMCIS 2014 - Savannah, GA, United States
Duration: Aug 7 2014Aug 9 2014

Other

Other20th Americas Conference on Information Systems, AMCIS 2014
CountryUnited States
CitySavannah, GA
Period8/7/148/9/14

Fingerprint

social media
immigration
Competitive intelligence
reform
opinion leader
decision maker
social network
Predictive analytics
community

Keywords

  • 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

Cite this

Chung, W., Zeng, D., & O'Hanlon, N. (2014). Identifying influential users in social media: A study of U.S. Immigration reform. In 20th Americas Conference on Information Systems, AMCIS 2014 Association for Information Systems.

Identifying influential users in social media : A study of U.S. Immigration reform. / Chung, Wingyan; Zeng, Dajun; O'Hanlon, Nathan.

20th Americas Conference on Information Systems, AMCIS 2014. Association for Information Systems, 2014.

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

Chung, W, Zeng, D & O'Hanlon, N 2014, Identifying influential users in social media: A study of U.S. Immigration reform. in 20th Americas Conference on Information Systems, AMCIS 2014. Association for Information Systems, 20th Americas Conference on Information Systems, AMCIS 2014, Savannah, GA, United States, 8/7/14.
Chung W, Zeng D, O'Hanlon N. Identifying influential users in social media: A study of U.S. Immigration reform. In 20th Americas Conference on Information Systems, AMCIS 2014. Association for Information Systems. 2014
Chung, Wingyan ; Zeng, Dajun ; O'Hanlon, Nathan. / Identifying influential users in social media : A study of U.S. Immigration reform. 20th Americas Conference on Information Systems, AMCIS 2014. Association for Information Systems, 2014.
@inproceedings{c1a30b18a5264663b5e37d4abe5e362c,
title = "Identifying influential users in social media: A study of U.S. Immigration reform",
abstract = "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.",
keywords = "Business intelligence, Influence, Influential users, Predictive analytics, Social media analytics, Social network analysis, Text mining, U.S. Immigration reform",
author = "Wingyan Chung and Dajun Zeng and Nathan O'Hanlon",
year = "2014",
language = "English (US)",
booktitle = "20th Americas Conference on Information Systems, AMCIS 2014",
publisher = "Association for Information Systems",

}

TY - GEN

T1 - Identifying influential users in social media

T2 - A study of U.S. Immigration reform

AU - Chung, Wingyan

AU - Zeng, Dajun

AU - O'Hanlon, Nathan

PY - 2014

Y1 - 2014

N2 - 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.

AB - 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.

KW - Business intelligence

KW - Influence

KW - Influential users

KW - Predictive analytics

KW - Social media analytics

KW - Social network analysis

KW - Text mining

KW - U.S. Immigration reform

UR - http://www.scopus.com/inward/record.url?scp=84905967888&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84905967888&partnerID=8YFLogxK

M3 - Conference contribution

AN - SCOPUS:84905967888

BT - 20th Americas Conference on Information Systems, AMCIS 2014

PB - Association for Information Systems

ER -