Catching Zika Fever: Application of Crowdsourcing and Machine Learning for Tracking Health Misinformation on Twitter

Abstract

In February 2016, World Health Organization declared the Zika outbreak a Public Health Emergency of International Concern. With developing evidence it can cause birth defects, and the Summer Olympics coming up in the worst affected country, Brazil, the virus caught fire on social media. In this work, use Zika as a case study in building a tool for tracking the misinformation around health concerns on Twitter. We collect more than 13 million tweets -spanning the initial reports in February 2016 and the Summer Olympics -regarding the Zika outbreak and track rumors outlined by the World Health Organization and Snopes fact checking website. The tool pipeline, which incorporates health professionals, crowdsourcing, and machine learning, allows us to capture health-related rumors around the world, as well as clarification campaigns by reputable health organizations. In the case of Zika, we discover an extremely bursty behavior of rumor-related topics, and show that, once the questionable topic is detected, it is possible to identify rumor-bearing tweets using automated techniques. Thus, we illustrate insights the proposed tools provide into potentially harmful information on social media, allowing public health researchers and practitioners to respond with a targeted and timely action.

Systematic Literature Review on the Spread of Health-related Misinformation on Social Media

“…Authors observe the distribution of useful and misleading information, and the pattern of consumption by different users. Some studies incorporated social network analysis or epidemiological modelling to better explain the dynamics of misinformation spread (Bessi et al, 2015;Ghenai and Mejova, 2017;Harris et al, 2014;Jin et al, 2014;Radzikowski et al, 2016;Wood, 2018). Many designs were also complemented by sentiment measures, for instance, the "antivaccine" sentiment (Bahk et al, 2016;Xu and Guo, 2018).…”

Fake Cures

“…Image sharing platforms such as Flickr and Instagram have become battlegrounds between the pro-anorexia movement and physicians attempting to intervene [13,92]. Uncertainty surrounding infectious disease outbreaks, such as the Zika epidemic of 2016, yielded rumors and speculations about its causes, preventive measures, and consequences [23,34].…”

“…Image sharing platforms such as Flickr and Instagram have become battlegrounds between the pro-anorexia movement and physicians attempting to intervene [13,92]. Uncertainty surrounding infectious disease outbreaks, such as the Zika epidemic of 2016, yielded rumors and speculations about its causes, preventive measures, and consequences [23,34].In this study we turn to the individuals sharing questionable medical information on Twitter, in particular cancer treatments which have been medically proven to be ineffective. Having around 336 million monthly active users in the first quarter of 2018 1 , Twitter is one of the largest social media websites expressly dedicated to the sharing of information, including that on cancer.…”

Information Sources and Needs in the Obesity and Diabetes Twitter Discourse

“…Moreover, Dunn et al [13] nd that prior exposure to opinions rejecting the safety or value of HPV vaccines is associated with an increased relative risk of posting similar opinions on Twitter. Recently, a tool combining crowdsourcing and text classi cation has been proposed to track misinformation on Twitter on the topic of Zika [18]. Another tool was proposed for crawling medical content from websites, blogs, and social media using sentiment and credibility scoring [1].…”