TY - GEN
T1 - Examining online vaccination discussion and communities in Twitter
AU - Yuan, Xiaoyi
AU - Crooks, Andrew T.
N1 - Publisher Copyright:
© 2018 Copyright is held by the owner/author(s).
PY - 2018/7/18
Y1 - 2018/7/18
N2 - Many states in the US allow a “belief exemption” for measles, mumps, and rubella (MMR) vaccines. People’s opinion on whether or not to take the vaccine could have direct consequences in public health— once the vaccine refusal of a group within a population is higher than what herd immunity can tolerate, a disease can transmit fast causing large scale of disease outbreaks. Social media has been one of the dominant communication channels for people to express their opinions of vaccination. Despite governmental organizations’ efforts of disseminating information of vaccination benefits, anti-vaccine sentiment is still gaining its momentum, especially on social media. This research investigates the communicative patterns of anti-vaccine and pro-vaccine users in Twitter by studying the retweet network from 660,892 tweets related to MMR vaccine published by 269,623 users after the 2015 California Disneyland measles outbreak. Using supervised learning, we classified the users into anti-vaccination, neutral to vaccination, and pro-vaccination groups. Using a combination of opinion groups and retweet network structural community detection, we discovered that pro- and anti-vaccine users retweet predominantly from their own opinion group, while users with neutral opinions are distributed across communities. For most cross-group communication, it was found that pro-vaccination users were retweeting anti-vaccination users than vice-versa. The paper concludes that anti-vaccine Twitter users are highly clustered and enclosed communities, and this makes it difficult for health organizations to penetrate and counter opinionated information. We believe that this finding may be useful in developing strategies for health communication of vaccination and overcome some the limits of current strategies.
AB - Many states in the US allow a “belief exemption” for measles, mumps, and rubella (MMR) vaccines. People’s opinion on whether or not to take the vaccine could have direct consequences in public health— once the vaccine refusal of a group within a population is higher than what herd immunity can tolerate, a disease can transmit fast causing large scale of disease outbreaks. Social media has been one of the dominant communication channels for people to express their opinions of vaccination. Despite governmental organizations’ efforts of disseminating information of vaccination benefits, anti-vaccine sentiment is still gaining its momentum, especially on social media. This research investigates the communicative patterns of anti-vaccine and pro-vaccine users in Twitter by studying the retweet network from 660,892 tweets related to MMR vaccine published by 269,623 users after the 2015 California Disneyland measles outbreak. Using supervised learning, we classified the users into anti-vaccination, neutral to vaccination, and pro-vaccination groups. Using a combination of opinion groups and retweet network structural community detection, we discovered that pro- and anti-vaccine users retweet predominantly from their own opinion group, while users with neutral opinions are distributed across communities. For most cross-group communication, it was found that pro-vaccination users were retweeting anti-vaccination users than vice-versa. The paper concludes that anti-vaccine Twitter users are highly clustered and enclosed communities, and this makes it difficult for health organizations to penetrate and counter opinionated information. We believe that this finding may be useful in developing strategies for health communication of vaccination and overcome some the limits of current strategies.
KW - Anti-vaccine movement
KW - Opinion classification
KW - Social media
KW - Twitter
UR - https://www.scopus.com/pages/publications/85051545002
U2 - 10.1145/3217804.3217912
DO - 10.1145/3217804.3217912
M3 - Conference contribution
AN - SCOPUS:85051545002
SN - 9781450363341
T3 - ACM International Conference Proceeding Series
SP - 197
EP - 206
BT - Proceedings of the 9th International Conference on Social Media and Society, SMSociety 2018
PB - Association for Computing Machinery
T2 - 9th International Conference on Social Media and Society, SMSociety 2018
Y2 - 18 July 2018 through 20 July 2018
ER -