4.6 Article

Real-time Twitter interactions during World Breastfeeding Week: A case study and social network analysis

期刊

PLOS ONE
卷 16, 期 3, 页码 -

出版社

PUBLIC LIBRARY SCIENCE
DOI: 10.1371/journal.pone.0249302

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资金

  1. Larsson-Rosenquist Foundation
  2. Yankelovich Center For Social Science Research at UC San Diego

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Using social network theory-based metrics, this study analyzed real-time user interactions on Twitter during the 2020 World Breastfeeding Week, finding that participants formed more interconnected relationships and identifiable communities during the campaign. Influencers dominating the conversations were mainly from the scientific community, but some influencers from the general public also played a bridging role between the public and scientific community. The study showed that applying social network analysis allowed for a better understanding of the messaging and engagement dynamics of the breastfeeding campaign across different communities and influencers.
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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