TY - JOUR
T1 - Does digital campaigning matter, and if so, how? Testing a broadcast versus network effects model of candidates Twitter use
AU - Gibson, Rachel
AU - Southern, Rosalynd
AU - Vaccari, Cristian
AU - Smyth, Peter
AU - Musayev, Jahandar
PY - 2024/8/9
Y1 - 2024/8/9
N2 - Studies of online campaigning have consistently demonstrated a positive impact on electoral success, but it remains unclear how this occurs. Some find the content and style of post matter, while others have pointed to overall activity as the key driver, promoting a “broadcast” effect model. Still, others have argued for indirect effects whereby candidates rely on followers to share content within their networks. This paper develops a “joined-up” model to test these arguments that includes new measures to capture the responsiveness of candidate tweets and the extent of user engagement. We apply the model to the 2017 UK General Election Twitter campaign. Our findings confirm a digital campaign effect, but in a two-step rather than direct manner. Specifically, candidates that attract more engagement with their tweets (likes and retweets) enjoy more electoral success. We expand on our findings to argue for a “network” rather than “broadcast” model of digital campaign effects.
AB - Studies of online campaigning have consistently demonstrated a positive impact on electoral success, but it remains unclear how this occurs. Some find the content and style of post matter, while others have pointed to overall activity as the key driver, promoting a “broadcast” effect model. Still, others have argued for indirect effects whereby candidates rely on followers to share content within their networks. This paper develops a “joined-up” model to test these arguments that includes new measures to capture the responsiveness of candidate tweets and the extent of user engagement. We apply the model to the 2017 UK General Election Twitter campaign. Our findings confirm a digital campaign effect, but in a two-step rather than direct manner. Specifically, candidates that attract more engagement with their tweets (likes and retweets) enjoy more electoral success. We expand on our findings to argue for a “network” rather than “broadcast” model of digital campaign effects.
KW - digital campaign
KW - elections
KW - machine learning
KW - network communication
KW - online mobilization
KW - Social media
KW - Twitter
UR - http://www.scopus.com/inward/record.url?scp=85200944711&partnerID=8YFLogxK
UR - https://candidates.democracyclub.org.uk/api/docs/csv/#past
UR - https://www.britishelectionstudy.com/data-objects/panel-study-data
UR - https://www.electoralcommission.org.uk/our-work/our-research/electoral-data/electoral-data-files-and-reports
U2 - 10.1080/19331681.2024.2387634
DO - 10.1080/19331681.2024.2387634
M3 - Article
AN - SCOPUS:85200944711
SN - 1933-1681
SP - 1
EP - 16
JO - Journal of Information Technology and Politics
JF - Journal of Information Technology and Politics
ER -