A Social Networks Approach to Understanding Vaccine Conversations on Twitter: Network Clusters, Sentiment, and Certainty in HPV Social Networks.

Individuals increasingly rely on the Internet, and social media in particular, for health-related information. A recent survey reports that 80% of Internet users search for health information online. In the present study, we employ Twitter data to understand content characteristics and the patterns of content flow of the conversations about the HPV vaccine debate. Approaching the HPV vaccine conversations on Twitter as a social network, we can identify key self-formed subgroups-clusters of users who create "siloes" of interactions and information flow. Combining network analysis, computer-aided content analysis, and human-coded content analysis, we explored the communication dynamics within the groups in terms of group members' affective and cognitive characteristics. Our findings show that positive emotion is positively correlated with cluster density, an indicator of strong ties and rapid information flow. In the case of negative emotion, we found that anger is a significant negative predictor for graph density. We also found a correlation between certainty and tentativeness; both at cluster as well as at tweet level, suggesting that clusters bring together people who are sure about the HPV vaccine and people who are exploring for answers.

Predicting Retweeting Behavior on Breast Cancer Social Networks: Network and Content Characteristics.

This study explored how social media, especially Twitter, serves as a viable place for communicating about cancer. Using a 2-step analytic method that combined social network analysis and computer-aided content analysis, this study investigated (a) how different types of network structures explain retweeting behavior and (b) which types of tweets are retweeted and why some messages generate more interaction among users. The analysis revealed that messages written by users who had a higher number of followers, a higher level of personal influence over the interaction, and closer relationships and similarities with other users were retweeted. In addition, a tweet with a higher level of positive emotion was more likely to be retweeted, whereas a tweet with a higher level of tentative words was less likely to be retweeted. These findings imply that Twitter can be an effective tool for the dissemination of health information. Theoretical and practical implications for psychosocial interventions for people with health concerns are discussed.

#Stupidcancer: Exploring a Typology of Social Support and the Role of Emotional Expression in a Social Media Community.

Social network sites (SNSs) like Twitter continue to attract users, many of whom turn to these spaces for social support for serious illnesses like cancer. Building on literature that explored the functionality of online spaces for health-related social support, we propose a typology that situates this type of support in an SNS-based open cancer community based on the type (informational or emotional) and the direction (expression or reception) of support. A content analysis applied the typology to a 2-year span of Twitter messages using the popular hashtag "#stupidcancer." Given that emotions form the basis for much of human communication and behavior, including aspects of social support, this content analysis also examined the relationship between emotional expression and online social support in tweets about cancer. Furthermore, this study looked at the various ways in which Twitter allows for message sharing across a user's entire network (not just among the cancer community). This work thus begins to lay the conceptual and empirical groundwork for future research testing the effects of various types of social support in open, interactive online cancer communities.

Stigma's Effect on Social Interaction and Social Media Activity.

Stigmatized topics, such as HIV/STD, likely constrain related information sharing in ways that should be apparent in social interactions both on and off the Internet. Specifically, the authors predicted that the more people perceive an issue as stigmatized, the less likely they are to talk about the issue both privately (with sexual partners and peers) and publicly (on Twitter). Study 1 tested the effect of stigma on conversations at the individual level: The authors asked a group of participants (N = 138) about perceived STD-testing stigma, interactions with a sexual partner, and conversations with peers about STD testing. Study 2 assessed whether health conditions, in the aggregate, were less likely to generate social media activity as a function of current stigmatization. Using 259,758 archived Twitter posts mentioning 13 medical conditions, the authors tested whether level of stigma predicted the volume of relevant social media conversation, controlling for each condition's amount of advocacy and Google search popularity from a user's perspective. Findings supported our hypotheses. Individuals who reported perceiving a given health conditions in more stigmatic ways also reported interacting less with others about that topic; Twitter results showed a similar pattern. Results also suggest a more complex story of influence, as funding from the National Institutes of Health (i.e., each conditions amount of advocacy) associated with the examined health conditions also predicted Twitter activity. Overall, these results indicated that stigma had a similar, dampening effect on face-to-face and Twitter interactions. Findings hold theoretical and practical implications, which are discussed.

Cancer talk on twitter: community structure and information sources in breast and prostate cancer social networks.

This study suggests taking a social networks theoretical approach to predict and explain patterns of information exchange among Twitter prostate and breast cancer communities. The authors collected profiles and following relationship data about users who posted messages about either cancer over 1 composite week. Using social network analysis, the authors identified the main clusters of interconnected users and their most followed hubs (i.e., information sources sought). Findings suggest that users who populated the persistent-across-time core cancer communities created dense clusters, an indication of taking advantage of the technology to form relationships with one another in ways that traditional one-to-many communication technologies cannot support. The major information sources sought were very specific to the community health interest and were grassroots oriented (e.g., a blog about prostate cancer treatments). Accounts associated with health organizations and news media, despite their focus on health, did not play a role in these core health communities. Methodological and practical implications for researchers and health campaigners are discussed.

Virtual Zika transmission after the first U.S. case: who said what and how it spread on Twitter.

BACKGROUND: This paper goes beyond detecting specific themes within Zika-related chatter on Twitter, to identify the key actors who influence the diffusive process through which some themes become more amplified than others. METHODS: We collected all Zika-related tweets during the 3 months immediately after the first U.S. case of Zika. After the tweets were categorized into 12 themes, a cross-section were grouped into weekly datasets, to capture 12 amplifier/user groups, and analyzed by 4 amplification modes: mentions, retweets, talkers, and Twitter-wide amplifiers. RESULTS: We analyzed 3,057,130 tweets in the United States and categorized 4997 users. The most talked about theme was Zika transmission (~58%). News media, public health institutions, and grassroots users were the most visible and frequent sources and disseminators of Zika-related Twitter content. Grassroots users were the primary sources and disseminators of conspiracy theories. CONCLUSIONS: Social media analytics enable public health institutions to quickly learn what information is being disseminated, and by whom, regarding infectious diseases. Such information can help public health institutions identify and engage with news media and other active information providers. It also provides insights into media and public concerns, accuracy of information on Twitter, and information gaps. The study identifies implications for pandemic preparedness and response in the digital era and presents the agenda for future research and practice.

Childhood Physical and Sexual Abuse and Social Network Patterns on Social Media: Associations With Alcohol Use and Problems Among Young Adult Women.

OBJECTIVE: The aim of the present study was to examine the links between severities of child abuse (physical vs. sexual), and alcohol use versus problems via social media (Facebook) peer connection structures. METHOD: A total of 318 undergraduate female students at a public university in the United States reported severity of child abuse experiences and current alcohol use and problems. Social network data were obtained directly from the individuals' Facebook network. RESULTS: Severity of childhood physical abuse was positively linked to alcohol use and problems via eigenvector centrality, whereas severity of childhood sexual abuse was negatively linked to alcohol use and problems via clustering coefficient. CONCLUSIONS: Childhood physical and sexual abuse were linked positively and negatively, respectively, to online social network patterns associated with alcohol use and problems. The study suggests the potential utility of these online network patterns as risk indices and ultimately using social media as a platform for targeted preventive interventions.

Twitter as a source of vaccination information: content drivers and what they are saying.

Twitter is a popular source of health information. This study reports a content analysis of posts about vaccinations, documenting sources, tone, and medical accuracy. Results can help explain patient knowledge and directions for educational campaigns. A set of 6,827 tweets indicates professional sources were shared most and treated positively. Two-thirds of shared medical content were substantiated. One-third of messages were positive, counter to other research and suggesting that users apply critical thinking when evaluating content.