Mapping out Violence Against Women of Influence on Twitter Using the Cyber-Lifestyle Routine Activity Theory.

The study applies and expands the routine activity theory to examine the dynamics of online harassment and violence against women on Twitter in India. We collected 931,363 public tweets (original posts and replies) over a period of 1 month that mentioned at least one of 101 influential women in India. By undertaking both manual and automated text analysis of "hateful" tweets, we identified three broad types of violence experienced by women of influence on Twitter: dismissive insults, ethnoreligious slurs, and gendered sexual harassment. The analysis also revealed different types of individually motivated offenders: "news junkies," "Bollywood fanatics," and "lone-wolves", who do not characteristically engage in direct targeted attacks against a single person. Finally, we question the effectiveness of Twitter's form of "guardianship" against online violence against women, as we found that a year after our initial data collection in 2017, only 22% of hostile posts with explicit forms of harassment have been deleted. We conclude that in the social media age, online and offline public spheres overlap and intertwine, requiring improved regulatory approaches, policies, and moderation tools of "capable" guardianship that empower women to actively participate in public life.

Measuring the impact of pharmacoepidemiologic research using altmetrics: A case study of a CNODES drug-safety article.

PURPOSE: To provide an overview of altmetrics, including their potential benefits and limitations, how they may be obtained, and their role in assessing pharmacoepidemiologic research impact. METHODS: Our review was informed by compiling relevant literature identified through searching multiple health research databases (PubMed, Embase, and CIHNAHL) and grey literature sources (websites, blogs, and reports). We demonstrate how pharmacoepidemiologists, in particular, may use altmetrics to understand scholarly impact and knowledge translation by providing a case study of a drug-safety study conducted by the Canadian Network of Observational Drug Effect Studies. RESULTS: A common approach to measuring research impact is the use of citation-based metrics, such as an article's citation count or a journal's impact factor. "Alternative" metrics, or altmetrics, are increasingly supported as a complementary measure of research uptake in the age of social media. Altmetrics are nontraditional indicators that capture a diverse set of traceable, online research-related artifacts including peer-reviewed publications and other research outputs (software, datasets, blogs, videos, posters, policy documents, presentations, social media posts, wiki entries, etc). CONCLUSION: Compared with traditional citation-based metrics, altmetrics take a more holistic view of research impact, attempting to capture the activity and engagement of both scholarly and nonscholarly communities. Despite the limited theoretical underpinnings, possible commercial influence, potential for gaming and manipulation, and numerous data quality-related issues, altmetrics are promising as a supplement to more traditional citation-based metrics because they can ingest and process a larger set of data points related to the flow and reach of scholarly communication from an expanded pool of stakeholders. Unlike citation-based metrics, altmetrics are not inherently rooted in the research publication process, which includes peer review; it is unclear to what extent they should be used for research evaluation.

Framework for Managing the COVID-19 Infodemic: Methods and Results of an Online, Crowdsourced WHO Technical Consultation.

BACKGROUND: An infodemic is an overabundance of information-some accurate and some not-that occurs during an epidemic. In a similar manner to an epidemic, it spreads between humans via digital and physical information systems. It makes it hard for people to find trustworthy sources and reliable guidance when they need it. OBJECTIVE: A World Health Organization (WHO) technical consultation on responding to the infodemic related to the coronavirus disease (COVID-19) pandemic was held, entirely online, to crowdsource suggested actions for a framework for infodemic management. METHODS: A group of policy makers, public health professionals, researchers, students, and other concerned stakeholders was joined by representatives of the media, social media platforms, various private sector organizations, and civil society to suggest and discuss actions for all parts of society, and multiple related professional and scientific disciplines, methods, and technologies. A total of 594 ideas for actions were crowdsourced online during the discussions and consolidated into suggestions for an infodemic management framework. RESULTS: The analysis team distilled the suggestions into a set of 50 proposed actions for a framework for managing infodemics in health emergencies. The consultation revealed six policy implications to consider. First, interventions and messages must be based on science and evidence, and must reach citizens and enable them to make informed decisions on how to protect themselves and their communities in a health emergency. Second, knowledge should be translated into actionable behavior-change messages, presented in ways that are understood by and accessible to all individuals in all parts of all societies. Third, governments should reach out to key communities to ensure their concerns and information needs are understood, tailoring advice and messages to address the audiences they represent. Fourth, to strengthen the analysis and amplification of information impact, strategic partnerships should be formed across all sectors, including but not limited to the social media and technology sectors, academia, and civil society. Fifth, health authorities should ensure that these actions are informed by reliable information that helps them understand the circulating narratives and changes in the flow of information, questions, and misinformation in communities. Sixth, following experiences to date in responding to the COVID-19 infodemic and the lessons from other disease outbreaks, infodemic management approaches should be further developed to support preparedness and response, and to inform risk mitigation, and be enhanced through data science and sociobehavioral and other research. CONCLUSIONS: The first version of this framework proposes five action areas in which WHO Member States and actors within society can apply, according to their mandate, an infodemic management approach adapted to national contexts and practices. Responses to the COVID-19 pandemic and the related infodemic require swift, regular, systematic, and coordinated action from multiple sectors of society and government. It remains crucial that we promote trusted information and fight misinformation, thereby helping save lives.

The lure of decentralized social media: Extending the UTAUT model for understanding users' adoption of blockchain-based social media.

The study uses 31 semi-structured interviews to explore users' motivations for adopting and using blockchain-based social media (BSM) platforms. The objective of the study is twofold-to collect empirical data on early adopters of BSM and to test the applicability of the Unified Theory of Acceptance and Use of Technology (UTAUT) model for explaining why some users are choosing BSM over mainstream social media (MSM) platforms. Manual content analysis of the interviews reveals that users are initially drawn to BSM due to social influence and financial incentives, but they continue to use it mainly because of the sense of community they experience. We also find that the steep learning curve, the absence of content moderation, as well as security and privacy concerns hinder the widespread adoption of these platforms. From the theoretical side, although the UTAUT model is generally suitable for examining why individuals use BSM, we suggest integrating two additional factors into the model: financial incentives and content moderation.

Enabling community through social media.

BACKGROUND: Social network analysis provides a perspective and method for inquiring into the structures that comprise online groups and communities. Traces from interaction via social media provide the opportunity for understanding how a community is formed and maintained online. OBJECTIVE: The paper aims to demonstrate how social network analysis provides a vocabulary and set of techniques for examining interaction patterns via social media. Using the case of the #hcsmca online discussion forum, this paper highlights what has been and can be gained by approaching online community from a social network perspective, as well as providing an inside look at the structure of the #hcsmca community. METHODS: Social network analysis was used to examine structures in a 1-month sample of Twitter messages with the hashtag #hcsmca (3871 tweets, 486 unique posters), which is the tag associated with the social media-supported group Health Care Social Media Canada. Network connections were considered present if the individual was mentioned, replied to, or had a post retweeted. RESULTS: Network analyses revealed patterns of interaction that characterized the community as comprising one component, with a set of core participants prominent in the network due to their connections with others. Analysis showed the social media health content providers were the most influential group based on in-degree centrality. However, there was no preferential attachment among people in the same professional group, indicating that the formation of connections among community members was not constrained by professional status. CONCLUSIONS: Network analysis and visualizations provide techniques and a vocabulary for understanding online interaction, as well as insights that can help in understanding what, and who, comprises and sustains a network, and whether community emerges from a network of online interactions.

To troll or not to troll: Young adults' anti-social behaviour on social media.

BACKGROUND: Online anti-social behaviour is on the rise, reducing the perceived benefits of social media in society and causing a number of negative outcomes. This research focuses on the factors associated with young adults being perpetrators of anti-social behaviour when using social media. METHOD: Based on an online survey of university students in Canada (n = 359), we used PLS-SEM to create a model and test the associations between four factors (online disinhibition, motivations for cyber-aggression, self-esteem, and empathy) and the likelihood of being a perpetrator of online anti-social behaviour. RESULTS: The model shows positive associations between two appetitive motives for cyber-aggression (namely recreation and reward) and being a perpetrator. This finding indicates that young adults engage in online anti-social behaviour for fun and social approval. The model also shows a negative association between cognitive empathy and being a perpetrator, which indicates that perpetrators may be engaging in online anti-social behaviour because they do not understand how their targets feel.

Social Media Interventions for Nutrition Education Among Adolescents: Scoping Review.

BACKGROUND: Adolescence is a critical period for reinforcing healthy dietary behaviors and supporting the development of cooking skills. Social media may be an avenue for supporting these behaviors, as it is popular among adolescents and can improve access to nutrition education interventions. This study sought to understand the optimal implementation of effective social media-based nutrition education interventions to inform the implementation of future social media-based nutrition education interventions. OBJECTIVE: A scoping review of the characteristics, feasibility, effectiveness, and factors influencing social media-based nutrition education interventions for adolescents was conducted. METHODS: We searched MEDLINE, Embase, CINAHL, Web of Science, and PsycINFO databases using a predefined search strategy. Primary research articles were independently screened and included if they involved adolescent populations (10-18 years old) and delivered nutrition education through social media. The information on intervention characteristics, feasibility, effectiveness, and factors influencing social media-based nutrition education interventions was extracted. RESULTS: A total of 28 publications out of 20,557 met the eligibility criteria. Twenty-five nutrition interventions were examined by 28 studies. Fourteen interventions used homegrown social media platforms, 8 used Facebook, and 2 used Instagram. Feasibility outcomes were infrequently reported, and the cost of intervention delivery was not reported. Engagement with interventions was variable; high engagement was not required to elicit significant improvements in dietary behaviors. Tailoring interventions, offering practical content, meaningful peer support, and involving families and communities facilitated successful interventions. Strategies to address engagement and technical issues were varied. CONCLUSIONS: Emerging evidence demonstrates that social media interventions for adolescent nutrition are acceptable and improve nutrition outcomes. Future interventions should strengthen peer support components and tailor delivery to specific populations. Further research should examine engagement, adherence, and the impact of interventions on behavioral and physical outcomes. This review is the first to examine the use of social media as the primary medium for nutrition education for adolescent populations. The analysis used in this review argues the importance of peer support in social media-based nutrition interventions and the need for user-centered design of the interventions.

From Facebook to YouTube: The Potential Exposure to COVID-19 Anti-Vaccine Videos on Social Media.

This article examines the role of Facebook and YouTube in potentially exposing people to COVID-19 vaccine-related misinformation. Specifically, to study the potential level of exposure, the article models a uni-directional information-sharing pathway beginning when a Facebook user encounters a vaccine-related post with a YouTube video, follows this video to YouTube, and then sees a list of related videos automatically recommended by YouTube. The results demonstrate that despite the efforts by Facebook and YouTube, COVID-19 vaccine-related misinformation in the form of anti-vaccine videos propagates on both platforms. Because of these apparent gaps in platform-led initiatives to combat misinformation, public health agencies must be proactive in creating vaccine promotion campaigns that are highly visible on social media to overtake anti-vaccine videos' prominence in the network. By examining related videos that a user potentially encounters, the article also contributes practical insights to identify influential YouTube channels for public health agencies to collaborate with on their public service announcements about the importance of vaccination programs and vaccine safety.

Measuring the Burden of Infodemics: Summary of the Methods and Results of the Fifth WHO Infodemic Management Conference.

Background: An infodemic is excess information, including false or misleading information, that spreads in digital and physical environments during a public health emergency. The COVID-19 pandemic has been accompanied by an unprecedented global infodemic that has led to confusion about the benefits of medical and public health interventions, with substantial impact on risk-taking and health-seeking behaviors, eroding trust in health authorities and compromising the effectiveness of public health responses and policies. Standardized measures are needed to quantify the harmful impacts of the infodemic in a systematic and methodologically robust manner, as well as harmonizing highly divergent approaches currently explored for this purpose. This can serve as a foundation for a systematic, evidence-based approach to monitoring, identifying, and mitigating future infodemic harms in emergency preparedness and prevention. Objective: In this paper, we summarize the Fifth World Health Organization (WHO) Infodemic Management Conference structure, proceedings, outcomes, and proposed actions seeking to identify the interdisciplinary approaches and frameworks needed to enable the measurement of the burden of infodemics. Methods: An iterative human-centered design (HCD) approach and concept mapping were used to facilitate focused discussions and allow for the generation of actionable outcomes and recommendations. The discussions included 86 participants representing diverse scientific disciplines and health authorities from 28 countries across all WHO regions, along with observers from civil society and global public health-implementing partners. A thematic map capturing the concepts matching the key contributing factors to the public health burden of infodemics was used throughout the conference to frame and contextualize discussions. Five key areas for immediate action were identified. Results: The 5 key areas for the development of metrics to assess the burden of infodemics and associated interventions included (1) developing standardized definitions and ensuring the adoption thereof; (2) improving the map of concepts influencing the burden of infodemics; (3) conducting a review of evidence, tools, and data sources; (4) setting up a technical working group; and (5) addressing immediate priorities for postpandemic recovery and resilience building. The summary report consolidated group input toward a common vocabulary with standardized terms, concepts, study designs, measures, and tools to estimate the burden of infodemics and the effectiveness of infodemic management interventions. Conclusions: Standardizing measurement is the basis for documenting the burden of infodemics on health systems and population health during emergencies. Investment is needed into the development of practical, affordable, evidence-based, and systematic methods that are legally and ethically balanced for monitoring infodemics; generating diagnostics, infodemic insights, and recommendations; and developing interventions, action-oriented guidance, policies, support options, mechanisms, and tools for infodemic managers and emergency program managers.

Investigating biomedical research literature in the blogosphere: a case study of diabetes and glycated hemoglobin (HbA1c).

OBJECTIVE: The research investigated the relationship between biomedical literature and blogosphere discussions about diabetes in order to explore the role of Web 2.0 technologies in disseminating health information. Are blogs that cite biomedical literature perceived as more trustworthy in the blogosphere, as measured by their popularity and interconnections with other blogs? METHODS: Web mining, social network analysis, and content analysis were used to analyze a large sample of blogs to determine how often biomedical literature is referenced in blogs on diabetes and how these blogs interconnect with others in the health blogosphere. RESULTS: Approximately 10% of the 3,005 blogs analyzed cite at least 1 article from the dataset of 2,246 articles. The most influential blogs, as measured by in-links, are written by diabetes patients and tend not to cite biomedical literature. In general, blogs that do not cite biomedical literature tend not to link to blogs that do. CONCLUSIONS: There is a large communication gap between health professional and personal diabetes blogs. Personal blogs do not tend to link to blogs by health professionals. Diabetes patients may be turning to the blogosphere for reasons other than authoritative information. They may be seeking emotional support and exchange of personal stories.

How coordinated link sharing behavior and partisans' narrative framing fan the spread of COVID-19 misinformation and conspiracy theories.

This study examines the presence and role of Coordinated Link Sharing Behavior (CLSB) on Facebook around the "America's Frontline Doctors" press conference, and the promotion of several unproven conspiracy theories including the false assertion that hydroxychloroquine is a "cure" for COVID-19 by Dr. Stella Immanuel, one of the doctors who took part in the press conference. We collected 7,737 public Facebook posts mentioning Stella Immanuel using CrowdTangle and then applied the specialized program CooRnet to detect CLSB among Facebook public pages, groups and verified profiles. Finally, we used a mixed-method approach consisting of both network and content analysis to examine the nature and scope of the detected CLSB. Our analysis shows how Facebook accounts engaged in CLSB to fuel the spread of misinformation. We identified a coalition of Facebook accounts that engaged in CLSB to promote COVID-19 related misinformation. This coalition included US-based pro-Trump, QAnon, and anti-vaccination accounts. In addition, we identified Facebook accounts that engaged in CLSB in other countries, such as Brazil and France, that primarily promoted hydroxychloroquine, and some accounts in African countries that criticized the government's pandemic response in their countries.

A Public Health Research Agenda for Managing Infodemics: Methods and Results of the First WHO Infodemiology Conference.

BACKGROUND: An infodemic is an overflow of information of varying quality that surges across digital and physical environments during an acute public health event. It leads to confusion, risk-taking, and behaviors that can harm health and lead to erosion of trust in health authorities and public health responses. Owing to the global scale and high stakes of the health emergency, responding to the infodemic related to the pandemic is particularly urgent. Building on diverse research disciplines and expanding the discipline of infodemiology, more evidence-based interventions are needed to design infodemic management interventions and tools and implement them by health emergency responders. OBJECTIVE: The World Health Organization organized the first global infodemiology conference, entirely online, during June and July 2020, with a follow-up process from August to October 2020, to review current multidisciplinary evidence, interventions, and practices that can be applied to the COVID-19 infodemic response. This resulted in the creation of a public health research agenda for managing infodemics. METHODS: As part of the conference, a structured expert judgment synthesis method was used to formulate a public health research agenda. A total of 110 participants represented diverse scientific disciplines from over 35 countries and global public health implementing partners. The conference used a laddered discussion sprint methodology by rotating participant teams, and a managed follow-up process was used to assemble a research agenda based on the discussion and structured expert feedback. This resulted in a five-workstream frame of the research agenda for infodemic management and 166 suggested research questions. The participants then ranked the questions for feasibility and expected public health impact. The expert consensus was summarized in a public health research agenda that included a list of priority research questions. RESULTS: The public health research agenda for infodemic management has five workstreams: (1) measuring and continuously monitoring the impact of infodemics during health emergencies; (2) detecting signals and understanding the spread and risk of infodemics; (3) responding and deploying interventions that mitigate and protect against infodemics and their harmful effects; (4) evaluating infodemic interventions and strengthening the resilience of individuals and communities to infodemics; and (5) promoting the development, adaptation, and application of interventions and toolkits for infodemic management. Each workstream identifies research questions and highlights 49 high priority research questions. CONCLUSIONS: Public health authorities need to develop, validate, implement, and adapt tools and interventions for managing infodemics in acute public health events in ways that are appropriate for their countries and contexts. Infodemiology provides a scientific foundation to make this possible. This research agenda proposes a structured framework for targeted investment for the scientific community, policy makers, implementing organizations, and other stakeholders to consider.

Examining algorithmic biases in YouTube's recommendations of vaccine videos.

OBJECTIVE: This research examines how YouTube recommends vaccination-related videos. MATERIALS AND METHODS: We used a social network analysis to evaluate how YouTube recommends vaccination related videos to its users. RESULTS: More pro-vaccine videos (64.75%) than anti-vaccine (19.98%) videos are on YouTube, with 15.27% of videos being neutral in sentiment. YouTube was more likely to recommend neutral and pro-vaccine videos than anti-vaccine videos. There is a homophily effect in which pro-vaccine videos were more likely to recommend other pro-vaccine videos than anti-vaccine ones, and vice versa. DISCUSSION: Compared to our prior study, the number of recommendations for pro-vaccine videos has significantly increased, suggesting that YouTube's demonization policy of harmful content and other changes to their recommender algorithm might have been effective in reducing the visibility of anti-vaccine videos. However, there are concerns that anti-vaccine videos are less likely to lead users to pro-vaccine videos due to the homophily effect observed in the recommendation network. CONCLUSION: The study demonstrates the influence of YouTube's recommender systems on the types of vaccine information users discover on YouTube. We conclude with a general discussion of the importance of algorithmic transparency in how social media platforms like YouTube decide what content to feature and recommend to its users.

Coding and Classifying Knowledge Exchange on Social Media: a Comparative Analysis of the #Twitterstorians and AskHistorians Communities.

As social media become a staple for knowledge discovery and sharing, questions arise about how self-organizing communities manage learning outside the domain of organized, authority-led institutions. Yet examination of such communities is challenged by the quantity of posts and variety of media now used for learning. This paper addresses the challenges of identifying (1) what information, communication, and discursive practices support successful online communities, (2) whether such practices are similar on Twitter and Reddit, and (3) whether machine learning classifiers can be successfully used to analyze larger datasets of learning exchanges. This paper builds on earlier work that used manual coding of learning and exchange in Reddit 'Ask' communities to derive a coding schema we refer to as 'learning in the wild'. This schema of eight categories: explanation with disagreement, agreement, or neutral presentation; socializing with negative, or positive intent; information seeking; providing resources; and comments about forum rules and norms. To compare across media, results from coding Reddit's AskHistorians are compared to results from coding a sample of #Twitterstorians tweets (n = 594). High agreement between coders affirmed the applicability of the coding schema to this different medium. LIWC lexicon-based text analysis was used to build machine learning classifiers and apply these to code a larger dataset of tweets (n = 69,101). This research shows that the 'learning in the wild' coding schema holds across at least two different platforms, and is partially scalable to study larger online learning communities.

Privacy Concerns and Self-Disclosure in Private and Public Uses of Social Media.

The study contributes to the ongoing debate about the "privacy paradox" in the context of using social media. The presence of a privacy paradox is often declared if there is no relationship between users' information privacy concerns and their online self-disclosure. However, prior research has produced conflicting results. The novel contribution of this study is that we consider public and private self-disclosure separately. The data came from a cross-national survey of 1,500 Canadians. For the purposes of the study, we only examined the subset of 545 people who had at least one public account and one private account. Going beyond a single view of self-disclosure, we captured five dimensions of self-disclosure: Amount, Depth, Polarity, Accuracy, and Intent; and two aspects of privacy concerns: concerns about organizational and social threats. To examine the collected data, we used Partial Least Squares Structural Equation Modeling. Our research does not support the presence of a privacy paradox as we found a relationship between privacy concerns from organizational and social threats and most of the dimensions of self-disclosure (even if the relationship was weak). There was no difference between patterns of self-disclosure on private versus public accounts. Different privacy concerns may trigger different privacy protection responses and, thus, may interact with self-disclosure differently. Concerns about organizational threats increase awareness and accuracy while reducing amount and depth, while concerns about social threats reduce accuracy and awareness while increasing amount and depth.

Social Media Content About Children's Pain and Sleep: Content and Network Analysis.

BACKGROUND: Social media is often used for health communication and can facilitate fast information exchange. Despite its increasing use, little is known about child health information sharing and engagement over social media. OBJECTIVE: The primary objectives of this study are to systematically describe the content of social media posts about child pain and sleep and identify the level of research evidence in these posts. The secondary objective is to examine user engagement with information shared over social media. METHODS: Twitter, Instagram, and Facebook were searched by members of the research team over a 2-week period using a comprehensive search strategy. Codes were used to categorize the content of posts to identify the frequency of content categories shared over social media platforms. Posts were evaluated by content experts to determine the frequency of posts consistent with existing research evidence. User engagement was analyzed using Netlytic, a social network analysis program, to examine visual networks illustrating the level of user engagement. RESULTS: From the 2-week period, nearly 1500 pain-related and 3800 sleep-related posts were identified and analyzed. Twitter was used most often to share knowledge about child pain (639/1133, 56.40% of posts), and personal experiences for child sleep (2255/3008, 75.00% of posts). For both topics, Instagram posts shared personal experiences (53/68, 78% pain; 413/478, 86.4% sleep), Facebook group posts shared personal experiences (30/49, 61% pain; 230/345, 66.7% sleep) and Facebook pages shared knowledge (68/198, 34.3% pain; 452/1026, 44.05% sleep). Across platforms, research evidence was shared in 21.96% (318/1448) of pain- and 9.16% (445/4857) of sleep-related posts; 5.38% (61/1133) of all pain posts and 2.82% (85/3008) of all sleep posts shared information inconsistent with the evidence, while the rest were absent of evidence. User interactions were indirect, with mostly one-way, rather than reciprocal conversations. CONCLUSIONS: Social media is commonly used to discuss child health, yet the majority of posts do not contain research evidence, and user engagement is primarily one-way. These findings represent an opportunity to expand engagement through open conversations with credible sources. Research and health care communities can benefit from incorporating specific information about evidence within social media posts to improve communication with the public and empower users to distinguish evidence-based content better. Together, these findings have identified potential gaps in social media communication that may be informative targets to guide future strategies for improving the translation of child health evidence over social media.