TY - GEN
T1 - Effective Messaging on Social Media
T2 - 31st ACM World Wide Web Conference, WWW 2022
AU - Mousavi, Maryam
AU - Davulcu, Hasan
AU - Ahmadi, Mohsen
AU - Axelrod, Robert
AU - Davis, Richard
AU - Atran, Scott
N1 - Funding Information:
This work was done while N.J. was a intern at Amazon Search. In addition, N. J. and Y. X. disclose support from NSF grants IIS-1850243, CCF-1918327. We thank reviewers for their comments.
Funding Information:
For support we thank the US Department of Defense Minerva Initiative and the Air Force Office of Scientific Research.
Publisher Copyright:
© 2022 ACM.
PY - 2022/4/25
Y1 - 2022/4/25
N2 - In this paper, we propose and test three content-based hypotheses that significantly increase message virality. We measure virality as the retweet counts of messages in a pair of real-world Twitter datasets A large dataset - UK Brexit with 51 million tweets from 2.8 million users between June 1, 2015 and May 12, 2019 and a smaller dataset - Nord Stream 2 with 516,000 tweets from 250,000 users between October 1, 2019 and October 15, 2019. We hypothesize, test and conclude that messages incorporating "negativity bias", "causal arguments"and "threats to personal or societal core values of target audiences"singularly and jointly increase message virality on social media.
AB - In this paper, we propose and test three content-based hypotheses that significantly increase message virality. We measure virality as the retweet counts of messages in a pair of real-world Twitter datasets A large dataset - UK Brexit with 51 million tweets from 2.8 million users between June 1, 2015 and May 12, 2019 and a smaller dataset - Nord Stream 2 with 516,000 tweets from 250,000 users between October 1, 2019 and October 15, 2019. We hypothesize, test and conclude that messages incorporating "negativity bias", "causal arguments"and "threats to personal or societal core values of target audiences"singularly and jointly increase message virality on social media.
KW - Causal Arguments
KW - Core Values
KW - Message Effectiveness
KW - Message Virality
KW - Negativity Bias
UR - http://www.scopus.com/inward/record.url?scp=85129792853&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85129792853&partnerID=8YFLogxK
U2 - 10.1145/3485447.3512016
DO - 10.1145/3485447.3512016
M3 - Conference contribution
AN - SCOPUS:85129792853
T3 - WWW 2022 - Proceedings of the ACM Web Conference 2022
SP - 2957
EP - 2966
BT - WWW 2022 - Proceedings of the ACM Web Conference 2022
PB - Association for Computing Machinery, Inc
Y2 - 25 April 2022 through 29 April 2022
ER -