Abstract—First identified 50 years ago, the Zika virus has
recently made global headlines due to a high profile outbreak in
Brazil coinciding with the Olympics. Mentions of Zika on social
media platforms exploded following initial reports of the
outbreak, and this unprecedented surge of heterogeneous data
can be processed using Big Data analysis techniques to acquire
further insights and knowledge into general public opinion.
Twitter data streams have previously been used to predict
outcomes of real world events. Twitter data filtered for the
keyword “Zika” was subjected to analysis using a sentiment
analysis lexicon-based framework to establish the polarity of
the messages. The World Health Organization (WHO)
recommends avoiding exposure to Zika-infected mosquitoes as
the most effective approach to prevention. The diffusion of
Twitter messages citing the WHO recommendations is analyzed
to help public health professionals and health agencies
formulate an effective response. Our results show that the
WHO recommendations were largely ignored in Twitter-based
discussions related to the Zika virus.
Index Terms—Zika virus, sentiment analysis, social media, twitter, vector control, big data.
The authors are with the Department of Industrial Engineering and Management, Yuan Ze University, Taiwan, ROC (e-mail:firstname.lastname@example.org, email@example.com).
Cite: Chuan-Jun Su and Jorge A. Quan Yon, "Sentiment Analysis and Information Diffusion on Social Media: The Case of the Zika Virus," International Journal of Information and Education Technology vol. 8, no. 9, pp. 685-692, 2018.