Breastfeeding Communication Strategies, Challenges and Opportunities in the Twitter-Verse: Perspectives of Influencers and Social Network Analysis.
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ABSTRACT:
SUBMITTER: Moukarzel S
PROVIDER: S-EPMC8230232 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Breastfeeding is one of many health practices known to support the survival and health of mother and infant, yet low breastfeeding rates persist globally. These rates may be influenced by limited diffusion of evidence-based research and guidelines from the scientific community (SC). As recently highlighted by the National Academy of Sciences, there is a need for the SC to diffuse its findings to the public more effectively online, as means to counteract the spread of misinformation. In response to this call, we gathered data from Twitter for one month from major breastfeeding hashtags resulting in an interconnected social network (n = 3,798 users). We then identified 59 influencers who disproportionately influenced information flow using social network analysis. These influencers were from the SC (e.g. academics, researchers, health care practitioners), as well as interested citizens (IC) and companies. We then conducted an ego-network analysis of influencer networks, developed ego maps, and compared diffusion metrics across the SC, IC and company influencers. We also qualitatively analyzed their tweets (n = 711) to understand the type of information being diffused. SC influencers were the least efficient communicators. Although having the highest tweeting activity (80% of tweets), they did not reach more individuals compared to IC and companies (two-step ego size: 220± 99, 188 ± 124, 169 ± 97 respectively, P = 0.28). Content analysis of tweets suggest IC are more active than the SC in diffusing evidence-based breastfeeding knowledge, with 35% of their tweets around recent research findings compared to only 12% by the SC. Nonetheless, in terms of outreach to the general public, the two-step networks of SC influences were more heterogenous than ICs (55.7 ± 5.07, 50.9 ± 12.0, respectively, P<0.001). Collectively, these findings suggest SC influencers may possess latent potential to diffuse research and evidence- based practices. However, the research suggests specific ways to enhance diffusion.
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Project description:The importance of breastfeeding for maternal and infant health is well-established, yet complex and intertwined sociocultural barriers contribute to suboptimal breastfeeding rates in most countries. Large-scale campaigns for evidence dissemination and promotion through targeted interventions on social media may help overcome some of these barriers. To date, most breastfeeding research on social media only focuses on content analysis, and there remains limited knowledge about the social networks of online communities (who interacts with whom), influencers in the breastfeeding space and the diffusion of evidence-based knowledge. This study, grounded in social network theory, aims to better understand the breastfeeding communication landscape on Twitter including determining the presence of a breastfeeding network, communities and key influencers. Further, we characterize influencer interactions, roles and the content being shared. The study revealed an overall breastfeeding social network of 3,798 unique individuals (users) and 3,972 tweets with commonly used hashtags (e.g., #breastfeeding and #normalizebreastfeeding). Around one third of users (n = 1,324, 34%) exchanged pornographic content (PC) that sexualized breastfeeding. The non-PC network (n = 2,474 users) formed 144 unique communities, and content flowing within the network was disproportionately influenced by 59 key influencers. However, these influencers had mostly inward-oriented interaction (% composition, E-I index: 47% professionals, -0.18; 41% interested citizens, -0.67; 12% companies, -0.18), limiting opportunities for evidence-based dissemination to the lay public. Although more tweets about peer-reviewed research findings were sent compared with tweets about nonevidence-based lay recommendations, our findings suggest that it is the lay public who often communicated findings, which may be overcome through a targeted social network-based intervention.
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Project description:Using Twitter to implement public health awareness campaigns is on the rise, but campaign monitoring and evaluation are largely dependent on basic Twitter Analytics. To establish the potential of social network theory-based metrics in better understanding public health campaigns, we analyzed real-time user interactions on Twitter during the 2020 World Breastfeeding Week (WBW) as an exemplar case. Social network analysis (SNA), including community and influencer identification, as well as topic modeling were used to compare the activity of n = 29,958 campaign participants and n = 10,694 reference users from the six-months pre-campaign period. Users formed more inter-connected relationships during the campaign, retweeting and mentioning each other 46,161 times compared to 10,662 times in the prior six months. Campaign participants formed identifiable communities that were not only based on their geolocation, but also based on interests and professional background. While influencers who dominated the WBW conversations were disproportionally members of the scientific community, the campaign did mobilize influencers from the general public who seemed to play a "bridging" role between the public and the scientific community. Users communicated about the campaign beyond its original themes to also discuss breastfeeding within the context of social and racial inequities. Applying SNA allowed understanding of the breastfeeding campaign's messaging and engagement dynamics across communities and influencers. Moving forward, WBW could benefit from improving targeting to enhance geographic coverage and user interactions. As this exemplar case indicates, social network theory and analysis can be used to inform other public health campaigns with data on user interactions that go beyond traditional metrics.
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