COVID-19 and the 5G conspiracy theory: social network analysis of twitter data

Background: Since the beginning of December 2019, the coronavirus disease (COVID-19) has spread rapidly around the world, which has led to increased discussions across online platforms. These conversations have also included various conspiracies shared by social media users. Amongst them, a popular theory has linked 5G to the spread of COVID-19, leading to misinformation and the burning of 5G towers in the United Kingdom. The understanding of the drivers of fake news and quick policies oriented to isolate and rebate misinformation are keys to combating it. Objective: The aim of this study is to develop an understanding of the drivers of the 5G COVID-19 conspiracy theory and strategies to deal with such misinformation. Methods: This paper performs a social network analysis and content analysis of Twitter data from a 7-day period (Friday, March 27, 2020, to Saturday, April 4, 2020) in which the #5GCoronavirus hashtag was trending on Twitter in the United Kingdom. Influential users were analyzed through social network graph clusters. The size of the nodes were ranked by their betweenness centrality score, and the graph's vertices were grouped by cluster using the Clauset-Newman-Moore algorithm. The topics and web sources used were also examined. Results: Social network analysis identified that the two largest network structures consisted of an isolates group and a broadcast group. The analysis also revealed that there was a lack of an authority figure who was actively combating such misinformation. Content analysis revealed that, of 233 sample tweets, 34.8% (n=81) contained views that 5G and COVID-19 were linked, 32.2% (n=75) denounced the conspiracy theory, and 33.0% (n=77) were general tweets not expressing any personal views or opinions. Thus, 65.2% (n=152) of tweets derived from nonconspiracy theory supporters, which suggests that, although the topic attracted high volume, only a handful of users genuinely believed the conspiracy. This paper also shows that fake news websites were the most popular web source shared by users; although, YouTube videos were also shared. The study also identified an account whose sole aim was to spread the conspiracy theory on Twitter. Conclusions: The combination of quick and targeted interventions oriented to delegitimize the sources of fake information is key to reducing their impact. Those users voicing their views against the conspiracy theory, link baiting, or sharing humorous tweets inadvertently raised the profile of the topic, suggesting that policymakers should insist in the efforts of isolating opinions that are based on fake news. Many social media platforms provide users with the ability to report inappropriate content, which should be used. This study is the first to analyze the 5G conspiracy theory in the context of COVID-19 on Twitter offering practical guidance to health authorities in how, in the context of a pandemic, rumors may be combated in the future

Research on Gang-Related Violence in the 21st Century

Conflict, including the threat or fear of potential violence, or being witness to or a victim of physical violence, constantly surrounds gangs and their communities and is the principal driver sustaining gang life. This Special Issue examines the diverse nature of gang-related violence with the goal of better understanding the growing complexities of gang violence over the last two decades to better inform public policy solutions. The contributions included in this Special Issue highlight the complex nature of gang-related violence in the 21st Century. As much as policy makers, the media, and even scholars like to simplify gang-related violence, all of the studies included in this Special Issue highlight the nuance and variation that exists

Denotation and connotations of biotechnology in Korean public opinion: a semantic network approach

This thesis tests how the frames and social representations of human embryonic stem cell research in South Korea could be visualized and measured by semantic network analysis. The contents of published articles take an eclectic approach to integrate sociological, social psychological, and semiological concepts and perspectives. By combining ethnographical and sociological approaches with applied semantic network analysis, concepts usually inferred and narrated by the researcher gain more vivid and intuitive visual representation along with mathematical substantiation. The methodology especially proposes indices to measure the most salient concepts that represent denotation and connotation out of the text corpus, and the ways to categorize themes more efficiently. The study concludes that the failure to establish a sustainable public relation and deliberative atmosphere regarding human embryonic stem cell research in South Korea is mainly due to polarized framings of opinion leading newspapers, progressive side’s incompetence to present an alternative agenda to economic development and suppressed discourses of lay people who strive for more transparent and just (scientific) governance. The semantic network represents the diverging core concepts of newspapers and people’s concealed motives in supporting the disgraced Korean scientist Woo-Suk Hwang and urges readers to deliberate on the scientific issue from a different perspective

Hyperpartisanship, Disinformation and Political Conversations on Twitter: The Brazilian Presidential Election of 2018

This paper examines the role of hyperpartisanship and polarization on Twitter during the 2018 Brazilian Presidential Election. Based on a mixed-methods approach, we collected and analyzed a dataset of over 8 million tweets about Jair Bolsonaro, a far-right candidate from the Social Liberty Party. Our results show that there is a strong connection between polarization, hyperpartisanship and disinformation. As the centrality of hyperpartisan outlets on Twitter grew, more traditional media outlets became less central and conversations became more polarized. We also confirmed that hyperpartisan outlets often shared disinformation or biased information, presented as a “truth-telling” alternative to journalistic outlets. And while disinformation was more frequently observed in the far-right group, it was also present in the anti-Bolsonaro cluster, especially towards the runoff period