A Sentiment Analysis of the 2014-15 Ebola Outbreak in the Media and Social Media-Reference-Cited by-同舟云学术

A Sentiment Analysis of the 2014-15 Ebola Outbreak in the Media and Social Media

Published:2022-06-10 Issue: Volume: Page:1923-1933
ISSN:
Container-title:Research Anthology on Implementing Sentiment Analysis Across Multiple Disciplines
language:
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Author:

John Blooma¹^ORCID,Baulch Bob²,Wickramasinghe Nilmini³^ORCID

Affiliation:

1. University of Canberra, Australia

2. International Food Policy Research Institute, Malawi

3. Swinburne University of Technology, Australia & Epworth HealthCare, Australia

Abstract

The negative and unbalanced nature of media and social media coverage has amplified anxieties and fears about the Ebola outbreak. The authors analyse news articles on the Ebola outbreak from two leading news outlets, together with comments on the articles from a well-known social media platform, from March 2014 to July 2015. The volume of news articles was greatest between August 2014 and January 2015, with a spike in October 2014, and was driven by the few cases of transmission in Europe and the USA. Sentiment analysis reveals coverage and commentary on the small number of Ebola cases in Europe and the USA were much more extensive than coverage and commentary on the outbreak in West Africa. Articles expressing negative sentiments were more common in the USA and also received more comments than those expressing positive sentiments. The negative sentiments expressed in the media and social media amplified fears about an Ebola outbreak outside West Africa, which increased pressure for unwarranted and wasteful precautionary measures.

Publisher

IGI Global

Reference37 articles.

1. Abbasi, A., Chen, H., Thoms, S., & Fu, T. (2008). Affect analysis of web forums and blogs using correlation ensembles. IEEE Transactions on Knowledge and Data Engineering, 20(9), 1168-1180.

2. Can Social Media Support Public Health? Demonstrating Disease Surveillance using Big Data Analytics;D.Asamoah;Proceedings of the Twenty-first Americas Conference on Information Systems,2015)

3. Baskerville, R., Baiyere, A., Gregor, S., Hevner, A., & Rossi, M. (2018). Design science research contributions: finding a balance between artifact and theory. Journal of the Association for Information Systems, 19(5), 358-376.

4. Improving Opinion Mining by Classifying Facts and Opinions in Twitter;S.Chatterjee;Proceedings of the American Conference on Information Systems,2017)

5. Chung, W., He, S., & Zeng, D. (2015). emood: Modeling emotion for social media analytics on Ebola disease outbreak. Proceedings of the International Conference on Information Systems.