Less reliable media drive interest in anti-vaccine information (original) (raw)
Related papers
Cureus
Introduction: COVID-19, known as coronavirus disease, has prompted a global reevaluation of societal norms. The World Health Organization (WHO) declared it a worldwide Public Health Emergency on January 30, 2020. Subsequently, governments and pharmaceutical firms developed vaccines, such as mRNA options from Pfizer and Moderna, alongside viral vector alternatives to combat the escalating COVID-19 case tally. Extensive inquiry was directed toward assessing vaccine efficiency. Nonetheless, vaccine discourse has surged across social media, prominently involving the anti-vaxxer community. This faction's hesitancy, rooted in reservations about efficacy, potential side effects, and conspiracy notions, contributes to an ongoing dialogue. Objective: This investigation delves into social media's role in proliferating COVID-19 misinformation, utilizing tools like Python, Excel, and external resources to craft data visuals that elucidate trends influencing misinformation dissemination and its hypothetical ties to elevated COVID-19 cases. Scrutiny of Twitter trends illuminates the prevalence of the hashtag #covidvaccine, although the platform curbs antivaccine hashtags. Result: Analysis of sentiment across 207,006 tweets reveals a prevailing positive sentiment toward COVID-19 vaccines, coexisting with lingering skepticism. Google trends reflect increased anti-vaccine ideology queries, notably post-FDA vaccine approval in December 2020, indicating public doubt. Conclusion: While limitations encompass data granularity, geographic origins of false tweets, bot account quantification on Twitter, and comprehensive digital resources, this study pioneers reference for forthcoming investigations. Its objective is to mitigate the diffusion of misinformation.
Revista Latina de Comunicación Social, 2021
Introduction: The debate on the Covid-19 vaccines has been very present on social networks since the very beginning of the health crisis, in a context of infodemics in which the presence of all kinds of information has been a breeding ground for misinformation or false news. Methodology: In this context, this article seeks to measure and characterize the conversation about Covid-19 vaccines on the social network Twitter. To this end, 62,045 tweets and 258,843 retweets from supporters and opponents of the vaccine were analyzed between December 2020 and February 2021. Results: The start of the vaccination campaign was the turning point at which pro-vaccine discourse began to take precedence over anti-vaccine discourse. Antivaccine groups are characterized by being strongly cohesive clusters, with an appreciable level of activity, but with less capacity to viralize content. Conclusions and discussion: Anti-vaccine discourses tend to rely on alternative media or content shared on social networks, which corroborates that quality information is one of the main measures against disinformation. It also highlights the role of quality or legacy media and the desirability of further developing anti-disinformation policies specific to the type of digital conversation taking place on Twitter.
A comparison between online social media discussions and vaccination rates: A tale of four vaccines
DIGITAL HEALTH, 2023
The recent COVID-19 pandemic has brought the debate around vaccinations to the forefront of public discussion. In this discussion, various social media platforms have a key role. While this has long been recognized, the way by which the public assigns attention to such topics remains largely unknown. Furthermore, the question of whether there is a discrepancy between people's opinions as expressed online and their actual decision to vaccinate remains open. To shed light on this issue, in this paper we examine the dynamics of online debates among four prominent vaccines (i.e., COVID-19, Influenza, MMR, and HPV) through the lens of public attention as captured on Twitter in the United States from 2015 to 2021. We then compare this to actual vaccination rates from governmental reports, which we argue serve as a proxy for real-world vaccination behaviors. Our results demonstrate that since the outbreak of COVID-19, it has come to dominate the vaccination discussion, which has led to a redistribution of attention from the other three vaccination themes. The results also show an apparent discrepancy between the online debates and the actual vaccination rates. These findings are in line with existing theories, that of agenda-setting and zero-sum theory. Furthermore, our approach could be extended to assess the public's attention toward other health-related issues, and provide a basis for quantifying the effectiveness of health promotion policies.
Removal of Anti-Vaccine Content Impacts Social Media Discourse
2022
Over the past several years, a growing number of social media platforms have begun taking an active role in content moderation and online speech regulation. While enforcement actions have been shown to improve outcomes within moderating platforms, less is known about possible spillover effects across platforms. We study the impact of removing groups promoting anti-vaccine content on Facebook on engagement with similar content on Twitter. We followed 160 Facebook groups discussing COVID-19 vaccines and prospectively tracked their removal from the platform between April and September 2021. We then identified users who cited these groups on Twitter, and examined their online behavior over time. Our findings from a stacked difference-indifferences analysis shows that users citing removed Facebook groups promoted more anti-vaccine content on Twitter in the month after the removals. In particular, users citing the removed groups used 10-33% more anti-vaccine keywords on Twitter, when compared to accounts citing groups that were not removed. Our results suggest that taking down anti-vaccine content on one platform can result in increased production of similar content on other platforms, raising questions about the overall effectiveness of these measures. CCS CONCEPTS • Information systems → Document representation; Social networks; Web mining; • Applied computing → Document management and text processing; Law, social and behavioral sciences.
Social Media + Society
Vaccine hesitancy has been a growing public health issue, but during COVID-19, understanding vaccine hesitancy and promote vaccine favorability takes on a troubling immediacy. With the growing political polarization on scientific issues, the COVID-19 vaccine-related sentiment has recently been divided across ideological lines. This study aims to understand how vaccine favorability and specific vaccine-related concerns including possible side effects, distrust in medical professionals, and conspiratorial beliefs concerning COVID-19 vaccines were articulated and transmitted by Twitter users from opposing ideological camps and with different follower scopes. Using a combination of computational approaches, including supervised machine-learning and structural topic modeling, we examined tweets surrounding COVID-19 vaccination ( N = 16,959) from 1 March to 30 June 2020. Results from linear mixed-effects models suggested that Twitter users high on conservative ideology and with a standard...
Human Vaccines & Immunotherapeutics, 2022
BACKGROUND/AIM The first case of COVID-19 in Turkey was officially recorded on March 11, 2020. Social media use increased worldwide, as well as in Turkey, during the pandemic, and conspiracy theories/fake news about medical complications of vaccines spread throughout the world. The aim of this study was to identify community interactions related to vaccines and to identify key influences/influencers before and after the pandemic using social network data from Twitter. MATERIALS AND METHODS Two datasets, including tweets about vaccinations before and after COVID-19 in Turkey, were collected. Social networks were created based on interactions (mentions) between Twitter users. Users and their influence were scored based on social network analysis and parameters that included in-degree and betweenness centrality. RESULTS In the pre-COVID-19 network, media figures and authors who had anti-vaccine views were the most influential users. In the post-COVID-19 network, the Turkish minister of health, the was the most influential figure. The vaccine network was observed to be growing rapidly after COVID-19, and the physicians and authors who had opinions about mandatory vaccinations received a great deal of reaction. One-way communication between influencers and other users in the network was determined. CONCLUSIONS This study shows the effectiveness and usefulness of large social media data for understanding public opinion on public health and vaccination in Turkey. The current study was completed before the implementation of the COVID-19 vaccine in Turkey. We anticipated that social network analysis would help reduce the "infodemic" before administering the vaccine and would also help public health workers act more proactively in this regard.
Analyzing the vaccination debate in social media data Pre- and Post-COVID-19 pandemic
International Journal of Applied Earth Observation and Geoinformation, 2022
The COVID-19 virus has caused and continues to cause unprecedented impacts on the life trajectories of millions of people globally. Recently, to combat the transmission of the virus, vaccination campaigns around the world have become prevalent. However, while many see such campaigns as positive (e.g., protecting lives), others see them as negative (e.g., the side effects that are not fully understood scientifically), resulting in diverse sentiments towards vaccination campaigns. In addition, the diverse sentiments have seldom been systematically quantified let alone their dynamic changes over space and time. To shed light on this issue, we propose an approach to analyze vaccine sentiments in space and time by using supervised machine learning combined with word embedding techniques. Taking the United States as a test case, we utilize a Twitter dataset (approximately 11.7 million tweets) from January 2015 to July 2021 and measure and map vaccine sentiments (Pro-vaccine, Anti-vaccine, and Neutral) across the nation. In doing so, we can capture the heterogeneous public opinions within social media discussions regarding vaccination among states. Results show how positive sentiment in social media has a strong correlation with the actual vaccinated population. Furthermore, we introduce a simple ratio between Anti and Pro-vaccine as a proxy to quantify vaccine hesitancy and show how our results align with other traditional survey approaches. The proposed approach illustrates the potential to monitor the dynamics of vaccine opinion distribution online, which we hope, can be helpful to explain vaccination rates for the ongoing COVID-19 pandemic.
An analysis of AstraZeneca COVID-19 vaccine misinformation and fear mongering on Twitter
From 50,080 tweets in the English language, we analysed the linked media sources and conducted a network detection study. Results: We found that the most frequently retweeted tweets were full of negative information, and in many cases came from media sources that are well-known for misinformation. Our analysis identified large coordination networks involved in political astroturfing and vaccine diplomacy in South Asia but also vaccine advocacy networks associated with European Commission employees. Conclusions: The results of this study show that Twitter discourse about #AstraZeneca is filled with misinformation and bad press, and may be distributed not only organically by anti-vaxxer activists but also systematically by professional sources.
Quantifying changes in vaccine coverage in mainstream media as a result of COVID-19 outbreak
medRxiv (Cold Spring Harbor Laboratory), 2021
Background: Achieving vaccine-derived herd immunity depends on public acceptance of vaccination, which in turn relies on people's understanding of its risks and benefits. The fundamental objective of public health messaging on vaccines is therefore the clear and concise communication of often complex information, and increasingly the countering of misinformation. The primary outlet shaping societal understanding is the mainstream online news media. There was widespread media coverage of the multiple vaccines that were rapidly developed in response to COVID-19. We studied vaccine coverage on the front pages of mainstream online news, using text-mining analysis to quantify the amount of information and sentiment polarization of vaccine coverage delivered to readers. Methods: We analyzed 28 million articles from 172 major news sources, across 11 countries between July 2015 and April 2021. We employed keyword-based frequency analysis to estimate the proportion of coverage given to vaccines in our dataset. We performed topic detection using BERTopic and Named Entity Recognition to identify the leading subjects and actors mentioned in the context of vaccines. We used the Vader Python module to perform sentiment polarization quantification of all our English-language articles. Results: We find that the proportion of headlines mentioning vaccines on the front pages of international major news sites increased from 0.1% to 3.8% with the outbreak of COVID-19. The absolute number of negatively polarized articles increased from a total of 6,698 before the COVID-19 outbreak 2015-2019 compared to 28,552 in 2020-2021. Overall, however, before the COVID-19 pandemic, vaccine coverage was slightly negatively polarized (57% negative) whereas with the outbreak, the coverage was primarily positively polarized (38% negative). Conclusions: Because of COVID-19, vaccines have risen from a marginal topic to a widely discussed topic on the front pages of major news outlets. Despite a perceived rise in .
Vaccines
Twitter is a useful source for detecting anti-vaccine content due to the increasing prevalence of these arguments on social media. We aimed to identify the prominent themes about vaccine hesitancy and refusal on social media posts in Turkish during the COVID-19 pandemic. In this qualitative study, we collected public tweets (n = 551,245) that contained a vaccine-related keyword and had been published between 9 December 2020 and 8 January 2021 through the Twitter API. A random sample of tweets (n = 1041) was selected and analyzed by four researchers with the content analysis method. We found that 90.5% of the tweets were about vaccines, 22.6% (n = 213) of the tweets mentioned at least one COVID-19 vaccine by name, and the most frequently mentioned COVID-19 vaccine was CoronaVac (51.2%). We found that 22.0% (n = 207) of the tweets included at least one anti-vaccination theme. Poor scientific processes (21.7%), conspiracy theories (16.4%), and suspicions towards manufacturers (15.5%) w...