In severe outbreaks such as Ebola, bird flu and SARS, people share news, and their thoughts and responses regarding the outbreaks on social media. Understanding how people perceive the severe outbreaks, what their responses are, and what factors affect these responses become important. In this paper, we conduct a comprehensive study of understanding and mining the spread of Ebola-related information on social media. In particular, we (i) conduct a large-scale data-driven analysis of geotagged social media messages to understand citizen reactions regarding Ebola; (ii) build information propagation models which measure locality of information; and (iii) analyze spatial, temporal and social properties of Ebola-related information. Our work provides new insights into Ebola outbreak by understanding citizen reactions and topic-based information propagation, as well as providing a foundation for analysis and response of future public health crises.
Background The 2014 Ebola epidemic in West Africa has attracted public interest worldwide, leading to millions of Ebola-related Internet searches being performed during the period of the epidemic. This study aimed to evaluate and interpret Google search queries for terms related to the Ebola outbreak both at the global level and in all countries where primary cases of Ebola occurred. The study also endeavoured to look at the correlation between the number of overall and weekly web searches and the number of overall and weekly new cases of Ebola. In October 2014, during heightened news coverage about cases of Ebola in the USA, anecdotal observations suggested that many Americans were anxious about Ebola. Given the negligible risk of infection, their anxiety was arguably driven by perceived rather than actual risk. Exaggeration or reassurance from the media can infl ame or subdue people’s perceived risk of Ebola infection. Fear can also be acquired by observation of other people’s experiences, as expressed on social media. Thus, social media amplifi ed fear about the imported Ebola case. As discussed in The Lancet Editorial (Nov 8, 2014), Twitter traffi c shows an imbalance across the digital divide; there were more tweets about Ebola in the USA, where transmission was contained, than in Guinea, Liberia, and Sierra Leone, where there was and remains a continuing epidemic. Despite the risk to most Americans being negligible, many people expressed anxiety. The figure shows how worldwide traffi c on Twitter and Google about Ebola increased as news spread about the fi rst US case and how they compare with influenza (flu)-related searches and tweets. Similar peaks were observed when other news about Ebola was released. In a random sample of tweets, we observed that the frequency of Ebola-related tweets associated with negative emotions, anxiety, anger, swearing, and death, as well as discrepant thinking (eg, shouldn’t), were higher than those associated with infl uenza (see fi gure in appendix). Twitter data can provide public health practitioners with a quantitative indicator of anxiety, anger, or negative emotions in the general public where Twitter penetration is high. This indicator could help to alleviate anxiety and correctly communicate the risk associated with Ebola. A diagnosis of Ebola on US soil triggered widespread panic. In response, the Centers for Disease Control and Prevention held a live Twitter chat to address public concerns. This study applied a textual analytics method to reveal insights from these tweets that can inform communication strategies. User-generated tweets were collected, sorted, and analyzed to reveal major themes. The public was concerned with symptoms and lifespan of the virus, disease transfer and contraction, safe travel, and protection of one's body. Abstract Objective Social media have strongly influenced awareness and perceptions of public health emergencies, but a considerable amount of social media content is now carried through images, rather than just text. This study's objective is to explore how image-sharing platforms are used for information dissemination in public health emergencies. Study design Retrospective review of images posted on two popular image-sharing platforms to characterize public discourse about Ebola. Methods Using the keyword ‘#ebola’ we identified a 1 sample of images posted on Instagram and Flickr across two sequential weeks in November 2014. Images from both platforms were independently coded by two reviewers and characterized by themes. We reviewed 1217 images posted on Instagram and Flickr and identified themes. Results Nine distinct themes were identified. These included: images of health care workers and professionals [308 (25 )], West Africa [75 (6 )], the Ebola virus [59 (5 )], and artistic renderings of Ebola [64 (5 )]. Also identified were images with accompanying embedded text related to Ebola and associated: facts [68 (6 )], fears [40 (3 )], politics [46 (4 )], and jokes [284 (23 )]. Several [273 (22 )] images were unrelated to Ebola or its sequelae. Instagram images were primarily coded as jokes [255 (42 )] or unrelated [219 (36 )], while Flickr images primarily depicted health care workers and other professionals [281 (46 )] providing care or other services for prevention or treatment. Conclusion Image sharing platforms are being used for information exchange about public health crises, like Ebola. Use differs by platform and discerning these differences can help inform future uses for health care professionals and researchers seeking to assess public fears and misinformation or provide targeted education awareness interventions.