TY - JOUR
T1 - Twitter Influencers in the 2016 US Congressional Races
AU - Shmargad, Yotam
N1 - Funding Information:
I want to thank students in my Spring 2017 Computational Social Science course at the University of Arizona, including Jordan Bruce, Zuleima Cota, Erman Gurses, Jeff Jensen, Colin Kyle, Don E. Merson, Lance Sacknoff, Farig Sadeque, Karthik Srinivasan, and Limin Zhang for their help with data collection. My deepest gratitude goes to Sam Puri and Limin Zhang for their help with additional processing of the data. I also greatly appreciate the feedback I received on this project from participants at the 2017 North American Social Networks conference, the 2018 Political Networks Conference, and the 2018 International Conference on Computational Social Science.
Publisher Copyright:
©, Copyright © Taylor & Francis Group, LLC.
PY - 2022
Y1 - 2022
N2 - In this paper, I outline a method for collecting Twitter data to identify two types of political actors that are increasingly prominent in social media environments: influential politicians and politicized influencers. Influential politicians are those whose messages are readily retweeted (i.e., shared) while politicized influencers are users who retweet politicians’ messages and who themselves receive many retweets. I find that highly retweeted politicized influencers tend not to have formal political affiliations, and so are politically influential but not in an official political capacity. I then relate the Twitter data to electoral outcomes of the 2016 US congressional races. I find that, for richer candidates and incumbents, receiving many retweets is associated with higher vote percentages while, for poorer candidates and challengers, receiving retweets from highly retweeted users is associated with higher vote percentages. Better-off candidates should thus strive to be influential politicians, whereas worse-off candidates should aim to get retweeted by influential users. I argue that the rise of social media begs for a study of what we might call influencer politics, which allows for new empirical investigations into the role that social media play in shaping the democratic process.
AB - In this paper, I outline a method for collecting Twitter data to identify two types of political actors that are increasingly prominent in social media environments: influential politicians and politicized influencers. Influential politicians are those whose messages are readily retweeted (i.e., shared) while politicized influencers are users who retweet politicians’ messages and who themselves receive many retweets. I find that highly retweeted politicized influencers tend not to have formal political affiliations, and so are politically influential but not in an official political capacity. I then relate the Twitter data to electoral outcomes of the 2016 US congressional races. I find that, for richer candidates and incumbents, receiving many retweets is associated with higher vote percentages while, for poorer candidates and challengers, receiving retweets from highly retweeted users is associated with higher vote percentages. Better-off candidates should thus strive to be influential politicians, whereas worse-off candidates should aim to get retweeted by influential users. I argue that the rise of social media begs for a study of what we might call influencer politics, which allows for new empirical investigations into the role that social media play in shaping the democratic process.
KW - campaign strategy
KW - celebrity politics
KW - everyday makers
KW - influencer politics
KW - social media
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U2 - 10.1080/15377857.2018.1513385
DO - 10.1080/15377857.2018.1513385
M3 - Article
AN - SCOPUS:85054796717
SN - 1537-7857
VL - 21
SP - 23
EP - 40
JO - Journal of Political Marketing
JF - Journal of Political Marketing
IS - 1
ER -