Sentiment Analysis and Information Diffusion on Social Media: The Case of the Zika Virus
Chuan‐Jun Su, Jorge A. Quan Yon · International Journal of Information and Education Technology · 2018
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.