TY - GEN
T1 - Information Adoption via Repeated or Diversified Social Influence on Twitter
AU - De Oliveira, Jaqueline Faria
AU - Marques-Neto, Humberto Torres
AU - Karsai, Marton
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2020/12/7
Y1 - 2020/12/7
N2 - Influence arriving via social ties may be relevant for a person to decide to buy a new product, share information, or to adopt a new behaviour. However, quantifying social influence is a difficult task, even in online social systems where the interactions and communication content can be closely followed. Here we study the information susceptibility and adoption thresholds of users on Twitter. We consider hashtag and retweet adoptions on different aggregation levels: items, users, and topic groups, and study these adoption mechanisms characterized by diversified or repeated influence stimuli. We find both metrics to be heterogeneously distributed, correlated, and dependent on the topics and aggregation level of social influence. We show that users adopt retweets easier than hashtags, and find that new influencing neighbors can effectively trigger adoptions. Our results may inform better models of adoption processes leading to a deeper empirical understanding of simple and complex contagion.
AB - Influence arriving via social ties may be relevant for a person to decide to buy a new product, share information, or to adopt a new behaviour. However, quantifying social influence is a difficult task, even in online social systems where the interactions and communication content can be closely followed. Here we study the information susceptibility and adoption thresholds of users on Twitter. We consider hashtag and retweet adoptions on different aggregation levels: items, users, and topic groups, and study these adoption mechanisms characterized by diversified or repeated influence stimuli. We find both metrics to be heterogeneously distributed, correlated, and dependent on the topics and aggregation level of social influence. We show that users adopt retweets easier than hashtags, and find that new influencing neighbors can effectively trigger adoptions. Our results may inform better models of adoption processes leading to a deeper empirical understanding of simple and complex contagion.
KW - Adoption Threshold
KW - Social Influence
KW - Susceptibility
UR - http://www.scopus.com/inward/record.url?scp=85103696315&partnerID=8YFLogxK
U2 - 10.1109/ASONAM49781.2020.9381365
DO - 10.1109/ASONAM49781.2020.9381365
M3 - Conference contribution
AN - SCOPUS:85103696315
T3 - Proceedings of the 2020 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2020
SP - 237
EP - 241
BT - Proceedings of the 2020 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2020
A2 - Atzmuller, Martin
A2 - Coscia, Michele
A2 - Missaoui, Rokia
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 12th IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2020
Y2 - 7 December 2020 through 10 December 2020
ER -