[en] Twitter users often crave more followers to increase their social popularity. While a variety of factors have been shown to attract the followers, very little work has been done to analyze the mechanism how Twitter users follow or unfollow each other. In this paper, we apply game theory to modeling the follow-unfollow mechanism on Twitter. We first present a two-player game which is based on the Prisoner’s Dilemma, and subsequently evaluate the payoffs when the two players adopt different strategies. To allow two players to play multiple rounds of the game, we propose a multi-stage game model. We design a Twitter bot analyzer which follows or unfollows other Twitter users by adopting the strategies from the multi-stage game. We develop an algorithm which enables the Twitter bot analyzer to automatically collect and analyze the data. The results from analyzing the data collected in our experiment show that the follow-back ratios for both of the Twitter bots are very low, which are 0.76% and 0.86%. This means that most of the Twitter users do not cooperate and only want to be followed instead of following others. Our results also exhibit the effect of different strategies on the follow-back followers and on the non-following followers as well.
Disciplines :
Ingénierie, informatique & technologie: Multidisciplinaire, généralités & autres
Auteur, co-auteur :
Chen, Jundong
Hossain, Md Shafaeat
BRUST, Matthias R. ; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT)
Johnson, Naomi
Co-auteurs externes :
yes
Langue du document :
Anglais
Titre :
A Game Theoretic Analysis of the Twitter Follow-Unfollow Mechanism
Date de publication/diffusion :
2018
Nom de la manifestation :
International Conference on Decision and Game Theory for Security
Organisateur de la manifestation :
Springer
Date de la manifestation :
2018
Titre de l'ouvrage principal :
International Conference on Decision and Game Theory for Security
Cha, M., Haddadi, H., Benevenuto, F., Gummadi, K.P.: Measuring user influence in Twitter: the million follower fallacy, In: ICWSM (2010)
Hutto, C., Yardi, S., Gilbert, E.: A longitudinal study of follow predictors on Twitter. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, CHI 2013, pp. 821–830. ACM, New York (2013)
Liu, L., Song, D., Tang, J., Liao, L., Li, X., Du, J.: FriendBurst: ranking people who get friends fast in a short time. Neurocomputing 210(C), 116–129 (2016)
Mueller, J., Stumme, G.: Predicting rising follower counts on Twitter using profile information. In: Proceedings of the 2017 ACM on Web Science Conference, WebSci 2017, pp. 121–130. ACM (2017)
Jajodia, S., Wang, H., Gianvecchio, S., Chu, Z.: Detecting automation of Twitter accounts: are you a human, bot, or cyborg? IEEE Trans. Dependable Secur. Comput. 9, 811–824 (2012)
Messias, J., Schmidt, L., Oliveira, R., Benevenuto, F.: You followed my bot! Transforming robots into influential users in Twitter. First Monday 18 (2013)
Chen, J., Kiremire, A.R., Brust, M.R., Phoha, V.V.: Modeling online social network users’ profile attribute disclosure behavior from a game theoretic perspective. Comput. Commun. 49, 18–32 (2014)
Chen, J., Kiremire, A.R., Brust, M.R., Phoha, V.V.: A game theoretic approach for modeling privacy settings of an online social network. EAI Endorsed Trans. Collab. Comput. 1(1–5), e4 (2014)
Surhone, L., Timpledon, M., Marseken, S.: Prisoner’s Dilemma: Game Theory, Merrill M. Albert W. Tucker, Framing Device, Experimental Economics. Betascript Publishing (2010)
Moses, J.: The follower’s dilemma, how game theory explains Twitter’s most important feature. https://www.linkedin.com/pulse/followers-dilemma-how-game-theory-explains-twitters-most-moses. Accessed 1 Feb 2016
Deshpande, D.: Twitter user classification with gensim and scikit-learn. In: The Python Conference, France (2016)
Zafarani, R., Abbasi, M.A., Liu, H.: Social Media Mining: An Introduction. Cambridge University Press, Cambridge (2014)
Kay, M.: Generating a network graph of Twitter followers using python and networkx. http://mark-kay.net/2014/08/15/network-graph-of-twitter-followers/. Accessed 15Aug 2014
Chen, J., Li, H., Wu, Z., Hossain, M.S.: Sentiment analysis of the correlation between regular tweets and retweets. In: Proceedings of the 16th IEEE International Symposium on Network Computing and Applications, pp. 1–5 (2017)