TY  - CHAP
A1  - Hagemann, Linus
A1  - Abramova, Olga
T1  - Crafting audience engagement in social media conversations
BT  - evidence from the U.S. 2020 presidential elections
T2  - Proceedings of the 55th Hawaii International Conference on System Sciences
N2  - Observing inconsistent results in prior studies, this paper applies the elaboration likelihood model to investigate the impact of affective and cognitive cues embedded in social media messages on audience engagement during a political event. Leveraging a rich dataset in the context of the 2020 U.S. presidential elections containing more than 3 million tweets, we found the prominence of both cue types. For the overall sample, positivity and sentiment are negatively related to engagement. In contrast, the post-hoc sub-sample analysis of tweets from famous users shows that emotionally charged content is more engaging. The role of sentiment decreases when the number of followers grows and ultimately becomes insignificant for Twitter participants with a vast number of followers. Prosocial orientation (“we-talk”) is consistently associated with more likes, comments, and retweets in the overall sample and sub-samples.
KW  - mediated conversation
KW  - big data
KW  - engagement
KW  - sentiment analysis
KW  - social media
Y1  - 2022
SN  - 978-0-9981331-5-7
SP  - 3222
EP  - 3231
PB  - HICSS Conference Office University of Hawaii at Manoa
CY  - Honolulu
ER  -