Social-Cyber Maneuvers Analysis During the COVID-19 Vaccine Initial Rollout

Allergy-like nocebo events reported with COVID-19 vaccines: a case control study

BACKGROUND

Allergy-like symptoms after COVID-19 vaccination are frequently reported, though true allergic reactions are rare. Clinical trials suggest many reported symptoms may reflect nocebo effects. This study aimed to characterize nocebo responses and identify associated factors.

RESEARCH DESIGN AND METHODS

A case-control study was conducted using pharmacovigilance records and a cross-sectional questionnaire. Cases were defined as patients reporting allergy-like symptoms without anaphylaxis; controls reported reactogenicity or localized reactions. Data on demographics, medical history, vaccinations, and psychological factors were analyzed using multivariate logistic regression to identify risk factors associated with nocebo effects.

RESULTS

Among 1038 participants, 320 were nocebo cases and 718 were controls. Cases frequently reported cutaneous (71.8%) and respiratory (38.8%) symptoms, with 43.4% occurring after the first dose. Nocebo responses were positively associated with a history of allergy (OR 1.78, 95% CI: 1.32-2.4) and COMIRNATY vaccine (OR 1.60, 95% CI: 1.20-2.14), and negatively correlated with perceived vaccine effectiveness (OR 0.93, 95% CI: 0.88-0.98).

CONCLUSIONS

The nocebo effect appears to differ by vaccine type and is more common in individuals with a history of allergy and lower perceived vaccine effectiveness. While further research is needed to validate these findings, this underscores the importance of clear, evidence-based communication to reduce nocebo responses.

Unraveling the Use of Disinformation Hashtags by Social Bots During the COVID-19 Pandemic: Social Networks Analysis

BACKGROUND

During the COVID-19 pandemic, social media platforms have been a venue for the exchange of messages, including those related to fake news. There are also accounts programmed to disseminate and amplify specific messages, which can affect individual decision-making and present new challenges for public health.

OBJECTIVE

This study aimed to analyze how social bots use hashtags compared to human users on topics related to misinformation during the outbreak of the COVID-19 pandemic.

METHODS

We selected posts on specific topics related to infodemics such as vaccines, hydroxychloroquine, military, conspiracy, laboratory, Bill Gates, 5G, and UV. We built a network based on the co-occurrence of hashtags and classified the posts based on their source. Using network analysis and community detection algorithms, we identified hashtags that tend to appear together in messages. For each topic, we extracted the most relevant subtopic communities, which are groups of interconnected hashtags.

RESULTS

The distribution of bots and nonbots in each of these communities was uneven, with some sets of hashtags being more common among accounts classified as bots or nonbots. Hashtags related to the Trump and QAnon social movements were common among bots, and specific hashtags with anti-Asian sentiments were also identified. In the subcommunities most populated by bots in the case of vaccines, the group of hashtags including #billgates, #pandemic, and #china was among the most common.

CONCLUSIONS

The use of certain hashtags varies depending on the source, and some hashtags are used for different purposes. Understanding these patterns may help address the spread of health misinformation on social media networks.

Emotional content and sharing on Facebook: A theory cage match

While emotional content predicts social media post sharing, competing theories of emotion imply different predictions about how emotional content will influence the virality of social media posts. We tested and compared these theoretical frameworks. Teams of annotators assessed more than 4000 multimedia posts from Polish and Lithuanian Facebook for more than 20 emotions. We found that, drawing on semantic space theory, modeling discrete emotions independently was superior to models examining valence (positive or negative), activation/arousal (high or low), or clusters of emotions and was on par with but had more explanatory power than a seven basic emotion model. Certain discrete emotions were associated with post sharing, including both positive and negative and relatively lower and higher activation/arousal emotions (e.g., amusement, cute/kama muta, anger, and sadness) even when controlling for number of followers, time up, topic, and Facebook angry reactions. These results provide key insights into better understanding of social media post virality.

Localizing COVID-19 Misinformation: A Case Study of Tracking Twitter Pandemic Narratives in Pennsylvania Using Computational Network Science

The recent COVID-19 outbreak has highlighted the importance of effective communication strategies to control the spread of the virus and debunk misinformation. By using accurate narratives, both online and offline, we can motivate communities to follow preventive measures and shape attitudes toward them. However, the abundance of misinformation stories can lead to vaccine hesitancy, obstructing the timely implementation of preventive measures, such as vaccination. Therefore, it is crucial to create appropriate and community-centered solutions based on regional data analysis to address mis/disinformation narratives and implement effective countermeasures specific to the particular geographic area.In this case study, we have attempted to create a research pipeline to analyze local narratives on social media, particularly Twitter, to identify misinformation spread locally, using the state of Pennsylvania as an example. Our proposed methodology pipeline identifies main communication trends and misinformation stories for the major cities and counties in southwestern PA, aiming to assist local health officials and public health specialists in instantly addressing pandemic communication issues, including misinformation narratives. Additionally, we investigated anti-vax actors' strategies in promoting harmful narratives. Our pipeline includes data collection, Twitter influencer analysis, Louvain clustering, BEND maneuver analysis, bot identification, and vaccine stance detection. Public health organizations and community-centered entities can implement this data-driven approach to health communication to inform their pandemic strategies.

Investigating coordinated account creation using burst detection and network analysis

Democracies around the world face the threat of manipulation of their electorates via coordinated online influence campaigns. Researchers have responded by developing valuable methods for finding automated accounts and identifying false information, but these valiant efforts often fall into a cat-and-mouse game with perpetrators who constantly change their behavior. This has forced several researchers to go beyond the detection of individual malicious actors by instead identifying the coordinated activity that propels potent information operations. In this vein, we provide rigorous quantitative evidence for the notion that sudden increases in Twitter account creations may provide early warnings of online information operations. Analysis of fourteen months of tweets discussing the 2020 U.S. elections revealed that accounts created during bursts exhibited more similar behavior, showed more agreement on mail-in voting and mask wearing, and were more likely to be bots and share links to low-credibility sites. In concert with other techniques for detecting nefarious activity, social media platforms could temporarily limit the influence of accounts created during these bursts. Given the advantages of combining multiple anti-misinformation methods, we join others in presenting a case for the need to develop more integrable methods for countering online influence campaigns.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1186/s40537-023-00695-7.

How disinformation operations against Russian opposition leader Alexei Navalny influence the international audience on Twitter

Previous research dedicated a lot of effort to investigation of the activities of the Internet Research Agency, a Russia-based troll factory, as well as other information operations. However, those studies are mostly focused on the 2016 U.S. presidential election, Brexit, and other major international political events. In this study, we have attempted to analyze how narratives about a domestic issue in Russia are used by malicious actors to promote harmful discourses globally and persuade an international audience on Twitter. We have identified bot and troll activities related to the Twitter discussions of a Russian opposition leader Alexei Navalny using social network analysis and bot detection. We have also implemented the BEND framework to find persuasion maneuvers that are used by bots in conversations about Navalny and found attempts to manipulate the opinion of the international audience on Twitter. Our findings have demonstrated that there is a significant presence of bot activities in information operations against Alexei Navalny as one of the leaders of the Russian opposition. We have observed how the Russian domestic issue is framed in the context of Russian confrontation with the West and how it is used to promote hostile narratives either against Navalny, an opposition movement, or democratic values. Many agents that we have identified pretend to be English speakers, who exhibit hostile attitudes towards Navalny and the Western democracies, express skepticism and distort the facts, promote a lack of trust in the democratic institutions as well as spread disinformation and conspiracy theories.

Social media and attitudes towards a COVID-19 vaccination: A systematic review of the literature

Background

Vaccine hesitancy continues to limit global efforts in combatting the COVID-19 pandemic. Emerging research demonstrates the role of social media in disseminating information and potentially influencing people's attitudes towards public health campaigns. This systematic review sought to synthesize the current evidence regarding the potential role of social media in shaping COVID-19 vaccination attitudes, and to explore its potential for shaping public health interventions to address the issue of vaccine hesitancy.

Methods

We performed a systematic review of the studies published from inception to 13 of March2022 by searching PubMed, Web of Science, Embase, PsychNET, Scopus, CINAHL, and MEDLINE. Studies that reported outcomes related to coronavirus disease 2019 (COVID-19) vaccine (attitudes, opinion, etc.) gathered from the social media platforms, and those analyzing the relationship between social media use and COVID-19 hesitancy/acceptance were included. Studies that reported no outcome of interest or analyzed data from sources other than social media (websites, newspapers, etc.) will be excluded. The Newcastle Ottawa Scale (NOS) was used to assess the quality of all cross-sectional studies included in this review. This study is registered with PROSPERO (CRD42021283219).

Findings

Of the 2539 records identified, a total of 156 articles fully met the inclusion criteria. Overall, the quality of the cross-sectional studies was moderate - 2 studies received 10 stars, 5 studies received 9 stars, 9 studies were evaluated with 8, 12 studies with 7,16 studies with 6, 11 studies with 5, and 6 studies with 4 stars. The included studies were categorized into four categories. Cross-sectional studies reporting the association between reliance on social media and vaccine intentions mainly observed a negative relationship. Studies that performed thematic analyses of extracted social media data, mainly observed a domination of vaccine hesitant topics. Studies that explored the degree of polarization of specific social media contents related to COVID-19 vaccines observed a similar degree of content for both positive and negative tone posted on different social media platforms. Finally, studies that explored the fluctuations of vaccination attitudes/opinions gathered from social media identified specific events as significant cofactors that affect and shape vaccination intentions of individuals.

Interpretation

This thorough examination of the various roles social media can play in disseminating information to the public, as well as how individuals behave on social media in the context of public health events, articulates the potential of social media as a platform of public health intervention to address vaccine hesitancy.

Funding

None.

Digital Marketing: A Unique Multidisciplinary Approach towards the Elimination of Viral Hepatitis

New technologies are supported by the global implementation of the internet. These improvements have deeply affected various disciplines of sciences and consequently changed services such as daily business, particularly health sectors. Innovative digital marketing strategies utilize the channels of social media and retrieved user data to analyze and improve relevant services. These multidisciplinary innovations can assist specialists, physicians and researchers in diagnostic, prophylaxis and treatment issues in the health sector. Accordingly, compared to recent decades, health decision makers are more accurate and trustful in defining new strategies. Interestingly, using social media and mobile health apps in current pandemics of SARS-CoV-2 could be an important instance of the key role of these platforms at the local and global level of health policies. These digital technologies provide platforms to connect public health sectors and health politicians for communicating and spreading relevant information. Adding influencers and campaigns to this toolbox strengthens the implementation of public health programs. In 2016, the WHO adopted a global program to eliminate viral hepatitis by 2030. Recent constructive measures that have been used in the battle against COVID-19 could be adopted for the elimination of viral hepatitis program. The presented evidence in our narrative review demonstrates that the application of digital marketing tools to create campaigns on social media, armed with professional influencers, can efficiently consolidate this program. The application of different strategies in using these popular tools will raise the public awareness about viral hepatitis. Subsequently, the availability of an effective vaccine for HBV and antiviral medication for HCV can motivate the audience to take steps towards prophylaxis and screening methods against these infectious illnesses. The encouragement of health policy makers to apply digital communication technologies and comprehensive roadmaps to implement this global program will certainly decrease the burden of viral hepatitis worldwide.