EMood

Modeling emotion for social media analytics on ebola disease outbreak

Wingyan Chung, Saike He, Dajun Zeng

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

Abstract

Social media enable users to express their emotion promptly, helping health policy makers to gauge public sentiment of disease outbreak. In this research, we developed an approach to social-media-based public health informatics and built a proof-of-concept system named eMood that helps to collect, analyze, and visualize Ebola outbreak discussions on Twitter. Our approach uses a comprehensive lexicon to identify emotion categories and present analysis findings of users' network relationship and influence patterns. We compared two methods of identifying user influence, user centrality and emotion entrainment, by using 255,118 tweets posted by 210,900 users in January 2015. Experimental results show that both methods identified highly influential users. Regression analysis of user influence rank and emotion scores demonstrates significant relationship between user influence and each emotion category. These results should provide strong implication for understanding social actions and for collecting social intelligence for public health informatics.

Original languageEnglish (US)
Title of host publication2015 International Conference on Information Systems
Subtitle of host publicationExploring the Information Frontier, ICIS 2015
PublisherAssociation for Information Systems
StatePublished - 2015
Event2015 International Conference on Information Systems: Exploring the Information Frontier, ICIS 2015 - Fort Worth, United States
Duration: Dec 13 2015Dec 16 2015

Other

Other2015 International Conference on Information Systems: Exploring the Information Frontier, ICIS 2015
CountryUnited States
CityFort Worth
Period12/13/1512/16/15

Fingerprint

Social Media
Public health
social media
emotion
Disease
Modeling
Regression analysis
Gages
Health
Public Health
public health
Entrainment
Emotion
Social media
twitter
Centrality
Regression Analysis
health policy
intelligence
Gauge

Keywords

  • Ebola disease outbreak
  • Emotion extraction
  • Influence measure
  • Public health informatics
  • Sentiment analysis
  • Social intelligence
  • Social media analytics
  • Social network analysis

ASJC Scopus subject areas

  • Computer Science Applications
  • Statistics, Probability and Uncertainty
  • Library and Information Sciences
  • Applied Mathematics

Cite this

Chung, W., He, S., & Zeng, D. (2015). EMood: Modeling emotion for social media analytics on ebola disease outbreak. In 2015 International Conference on Information Systems: Exploring the Information Frontier, ICIS 2015 Association for Information Systems.

EMood : Modeling emotion for social media analytics on ebola disease outbreak. / Chung, Wingyan; He, Saike; Zeng, Dajun.

2015 International Conference on Information Systems: Exploring the Information Frontier, ICIS 2015. Association for Information Systems, 2015.

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

Chung, W, He, S & Zeng, D 2015, EMood: Modeling emotion for social media analytics on ebola disease outbreak. in 2015 International Conference on Information Systems: Exploring the Information Frontier, ICIS 2015. Association for Information Systems, 2015 International Conference on Information Systems: Exploring the Information Frontier, ICIS 2015, Fort Worth, United States, 12/13/15.
Chung W, He S, Zeng D. EMood: Modeling emotion for social media analytics on ebola disease outbreak. In 2015 International Conference on Information Systems: Exploring the Information Frontier, ICIS 2015. Association for Information Systems. 2015
Chung, Wingyan ; He, Saike ; Zeng, Dajun. / EMood : Modeling emotion for social media analytics on ebola disease outbreak. 2015 International Conference on Information Systems: Exploring the Information Frontier, ICIS 2015. Association for Information Systems, 2015.
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