Brittany Seymour1, Rebekah Getman, Avinash Saraf, Lily H Zhang, Elsbeth Kalenderian. 1. Brittany Seymour and Elsbeth Kalenderian are with the Department of Oral Health Policy and Epidemiology, Harvard School of Dental Medicine, Boston, MA. Rebekah Getman is with the Harvard Global Health Institute, Cambridge, MA. Avinash Saraf and Lily H. Zhang are students at Harvard College, Cambridge, and interns at the Harvard Global Health Institute, Cambridge.
Abstract
OBJECTIVES: In an antifluoridation case study, we explored digital pandemics and the social spread of scientifically inaccurate health information across the Web, and we considered the potential health effects. METHODS: Using the social networking site Facebook and the open source applications Netvizz and Gephi, we analyzed the connectedness of antifluoride networks as a measure of social influence, the social diffusion of information based on conversations about a sample scientific publication as a measure of spread, and the engagement and sentiment about the publication as a measure of attitudes and behaviors. RESULTS: Our study sample was significantly more connected than was the social networking site overall (P<.001). Social diffusion was evident; users were forced to navigate multiple pages or never reached the sample publication being discussed 60% and 12% of the time, respectively. Users had a 1 in 2 chance of encountering negative and nonempirical content about fluoride unrelated to the sample publication. CONCLUSIONS: Network sociology may be as influential as the information content and scientific validity of a particular health topic discussed using social media. Public health must employ social strategies for improved communication management.
OBJECTIVES: In an antifluoridation case study, we explored digital pandemics and the social spread of scientifically inaccurate health information across the Web, and we considered the potential health effects. METHODS: Using the social networking site Facebook and the open source applications Netvizz and Gephi, we analyzed the connectedness of antifluoride networks as a measure of social influence, the social diffusion of information based on conversations about a sample scientific publication as a measure of spread, and the engagement and sentiment about the publication as a measure of attitudes and behaviors. RESULTS: Our study sample was significantly more connected than was the social networking site overall (P<.001). Social diffusion was evident; users were forced to navigate multiple pages or never reached the sample publication being discussed 60% and 12% of the time, respectively. Users had a 1 in 2 chance of encountering negative and nonempirical content about fluoride unrelated to the sample publication. CONCLUSIONS: Network sociology may be as influential as the information content and scientific validity of a particular health topic discussed using social media. Public health must employ social strategies for improved communication management.
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