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Social media in Ebola outbreak.

ABSTRACT: The West African 2014 Ebola outbreak has highlighted the need for a better information network. Hybrid information networks, an integration of both hierarchical and formalized command control-driven and community-based, or ad hoc emerging networks, could assist in improving public health responses. By filling the missing gaps with social media use, the public health response could be more proactive rather than reactive in responding to such an outbreak of global concern. This article provides a review of the current social media use specifically in this outbreak by systematically collecting data from ProQuest Newsstand, Dow Jones Factiva, Program for Monitoring Emerging Diseases (ProMED) as well as Google Trends. The period studied is from 19 March 2014 (first request for information on ProMED) to 15 October 2014, a total of 31 weeks. The term 'Ebola' was used in the search for media reports. The outcome of the review shows positive results for social media use in effective surveillance response mechanisms - for improving the detection, preparedness and response of the outbreak - as a complement to traditional, filed, work-based surveillance approach.

SUBMITTER: Hossain L

PROVIDER: S-EPMC9150578 | biostudies-literature | 2016 Jul

REPOSITORIES: biostudies-literature

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Social media in Ebola outbreak.

Hossain L L Kam D D Kong F F Wigand R T RT Bossomaier T T

Epidemiology and infection 20160304 10

The West African 2014 Ebola outbreak has highlighted the need for a better information network. Hybrid information networks, an integration of both hierarchical and formalized command control-driven and community-based, or ad hoc emerging networks, could assist in improving public health responses. By filling the missing gaps with social media use, the public health response could be more proactive rather than reactive in responding to such an outbreak of global concern. This article provides a ...[more]

PMID: 26939535

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Project description:BACKGROUND:The Ebola communication crisis of 2014 generated widespread fear and attention among Western news media, social media users, and members of the United States (US) public. Health communicators need more information on misinformation and the social media environment during a fear-inducing disease outbreak to improve communication practices. The purpose of this study was to describe the content of Ebola-related tweets with a specific focus on misinformation, political content, health related content, risk framing, and rumors. METHODS:We examined tweets from a random 1% sample of all tweets published September 30th - October 30th, 2014, filtered for English-language tweets mentioning "Ebola" in the content or hashtag, that had at least 1 retweet (N = 72,775 tweets). A randomly selected subset of 3639 (5%) tweets were evaluated for inclusion. We analyzed the 3113 tweets that meet inclusion criteria using public health trained human coders to assess tweet characteristics (joke, opinion, discord), veracity (true, false, partially false), political context, risk frame, health context, Ebola specific messages, and rumors. We assessed the proportion of tweets with specific content using descriptive statistics and chi-squared tests. RESULTS:Of non-joke tweets, 10% of Ebola-related tweets contained false or partially false information. Twenty-five percent were related to politics, 28% contained content that provoked reader response or promoted discord, 42% contained risk elevating messages and 72% were related to health. The most frequent rumor mentioned focused on government conspiracy. When comparing tweets with true information to tweets with misinformation, a greater percentage of tweets with misinformation were political in nature (36% vs 15%) and contained discord-inducing statements (45% vs 10%). Discord-inducing statements and political messages were both significantly more common in tweets containing misinformation compared with those without(p < 0.001). CONCLUSIONS:Results highlight the importance of anticipating politicization of disease outbreaks, and the need for policy makers and social media companies to build partnerships and develop response frameworks in advance of an event. While each public health event is different, our findings provide insight into the possible social media environment during a future epidemic and could help optimize potential public health communication strategies.

Project description:BackgroundWuhan, China, the epicenter of the COVID-19 pandemic, imposed citywide lockdown measures on January 23, 2020. Neighboring cities in Hubei Province followed suit with the government enforcing social distancing measures to restrict the spread of the disease throughout the province. Few studies have examined the emotional attitudes of citizens as expressed on social media toward the imposed social distancing measures and the factors that affected their emotions.ObjectiveThe aim of this study was twofold. First, we aimed to detect the emotional attitudes of different groups of users on Sina Weibo toward the social distancing measures imposed by the People's Government of Hubei Province. Second, the influencing factors of their emotions, as well as the impact of the imposed measures on users' emotions, was studied.MethodsSina Weibo, one of China's largest social media platforms, was chosen as the primary data source. The time span of selected data was from January 21, 2020, to March 24, 2020, while analysis was completed in late June 2020. Bi-directional long short-term memory (Bi-LSTM) was used to analyze users' emotions, while logistic regression analysis was employed to explore the influence of explanatory variables on users' emotions, such as age and spatial location. Further, the moderating effects of social distancing measures on the relationship between user characteristics and users' emotions were assessed by observing the interaction effects between the measures and explanatory variables.ResultsBased on the 63,169 comments obtained, we identified six topics of discussion-(1) delaying the resumption of work and school, (2) travel restrictions, (3) traffic restrictions, (4) extending the Lunar New Year holiday, (5) closing public spaces, and (6) community containment. There was no multicollinearity in the data during statistical analysis; the Hosmer-Lemeshow goodness-of-fit was 0.24 (χ28=10.34, P>.24). The main emotions shown by citizens were negative, including anger and fear. Users located in Hubei Province showed the highest amount of negative emotions in Mainland China. There are statistically significant differences in the distribution of emotional polarity between social distancing measures (χ220=19,084.73, P<.001), as well as emotional polarity between genders (χ24=1784.59, P<.001) and emotional polarity between spatial locations (χ24=1659.67, P<.001). Compared with other types of social distancing measures, the measures of delaying the resumption of work and school or travel restrictions mainly had a positive moderating effect on public emotion, while traffic restrictions or community containment had a negative moderating effect on public emotion.ConclusionsFindings provide a reference point for the adoption of epidemic prevention and control measures, and are considered helpful for government agencies to take timely actions to alleviate negative emotions during public health emergencies.

Project description:ObjectiveResearch studies show that social media may be valuable tools in the disease surveillance toolkit used for improving public health professionals' ability to detect disease outbreaks faster than traditional methods and to enhance outbreak response. A social media work group, consisting of surveillance practitioners, academic researchers, and other subject matter experts convened by the International Society for Disease Surveillance, conducted a systematic primary literature review using the PRISMA framework to identify research, published through February 2013, answering either of the following questions: Can social media be integrated into disease surveillance practice and outbreak management to support and improve public health?Can social media be used to effectively target populations, specifically vulnerable populations, to test an intervention and interact with a community to improve health outcomes?Examples of social media included are Facebook, MySpace, microblogs (e.g., Twitter), blogs, and discussion forums. For Question 1, 33 manuscripts were identified, starting in 2009 with topics on Influenza-like Illnesses (n = 15), Infectious Diseases (n = 6), Non-infectious Diseases (n = 4), Medication and Vaccines (n = 3), and Other (n = 5). For Question 2, 32 manuscripts were identified, the first in 2000 with topics on Health Risk Behaviors (n = 10), Infectious Diseases (n = 3), Non-infectious Diseases (n = 9), and Other (n = 10).ConclusionsThe literature on the use of social media to support public health practice has identified many gaps and biases in current knowledge. Despite the potential for success identified in exploratory studies, there are limited studies on interventions and little use of social media in practice. However, information gleaned from the articles demonstrates the effectiveness of social media in supporting and improving public health and in identifying target populations for intervention. A primary recommendation resulting from the review is to identify opportunities that enable public health professionals to integrate social media analytics into disease surveillance and outbreak management practice.

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Social media in Ebola outbreak.

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Social media in Ebola outbreak.

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