TY - GEN
T1 - Influence of Retweeting on the Behaviors of Social Networking Service Users
AU - Yan, Yizhou
AU - Toriumi, Fujio
AU - Sugawara, Toshiharu
N1 - Funding Information:
Acknowledgements. This work is partly supported by JSPS KAKENHI Grant Number 20H04245, 19H02376, 18H03498 and 17KT0044. We thank the Program Committee for their insightful comments.
Publisher Copyright:
© 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.
PY - 2021
Y1 - 2021
N2 - Retweeting is a featured mechanism of some social media platforms such as Twitter, Facebook, and Weibo. Users share articles with friends or followers by reposting a tweet. However, the ways in which retweeting affects the dominant behaviors of users is still unclear. Therefore, we investigate the influence of retweeting on the behaviors of social media users from a networked, game theoretic perspective; in other words, we attempt to clarify the ways in which the presence of a retweeting mechanism in social media promotes or diminishes the willingness of users toward posting articles and commenting. We propose a retweet reward game model that has been derived by adding a retweeting mechanism to a reward game, which is a simple social networking service model. Subsequently, we conduct some simulation-based experiments to understand the effects of retweeting on the behaviors of users. We observe that users are motivated to post new articles if there is a retweeting mechanism. Furthermore, agents in dense networks are motivated to comment on the articles posted by others because articles spread widely among users, and thus, users can be incentivized to post articles.
AB - Retweeting is a featured mechanism of some social media platforms such as Twitter, Facebook, and Weibo. Users share articles with friends or followers by reposting a tweet. However, the ways in which retweeting affects the dominant behaviors of users is still unclear. Therefore, we investigate the influence of retweeting on the behaviors of social media users from a networked, game theoretic perspective; in other words, we attempt to clarify the ways in which the presence of a retweeting mechanism in social media promotes or diminishes the willingness of users toward posting articles and commenting. We propose a retweet reward game model that has been derived by adding a retweeting mechanism to a reward game, which is a simple social networking service model. Subsequently, we conduct some simulation-based experiments to understand the effects of retweeting on the behaviors of users. We observe that users are motivated to post new articles if there is a retweeting mechanism. Furthermore, agents in dense networks are motivated to comment on the articles posted by others because articles spread widely among users, and thus, users can be incentivized to post articles.
KW - Agent-based simulation
KW - Complex networks
KW - Meta-norms game
KW - Retweeting
KW - Social media
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U2 - 10.1007/978-3-030-65347-7_56
DO - 10.1007/978-3-030-65347-7_56
M3 - Conference contribution
AN - SCOPUS:85098283725
SN - 9783030653460
T3 - Studies in Computational Intelligence
SP - 671
EP - 682
BT - Complex Networks and Their Applications IX - Volume 1, Proceedings of the Ninth International Conference on Complex Networks and Their Applications COMPLEX NETWORKS 2020
A2 - Benito, Rosa M.
A2 - Cherifi, Chantal
A2 - Cherifi, Hocine
A2 - Moro, Esteban
A2 - Rocha, Luis Mateus
A2 - Sales-Pardo, Marta
PB - Springer Science and Business Media Deutschland GmbH
T2 - 9th International Conference on Complex Networks and Their Application, COMPLEX NETWORKS 2020
Y2 - 1 December 2020 through 3 December 2020
ER -