A game theoretic analysis of the twitter follow-unfollow mechanism. Chen, J., Hossain, M. S., Brust, M. R., & Johnson, N. In Bushnell, L., Poovendran, R., & Başar, T., editors, Decision and Game Theory for Security, volume 11199, of Lecture Notes in Computer Science, pages 265–276, Cham, 2018. Springer International Publishing. Citation Key Alias: chenGameTheoreticAnalysis2018, pop00231 tex.type: [object Object]
A game theoretic analysis of the twitter follow-unfollow mechanism [link]Paper  doi  abstract   bibtex   
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%0.76%0.76\textbackslash% and 0.86%0.86%0.86\textbackslash%. 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.
@inproceedings{chen_game_2018,
	address = {Cham},
	series = {Lecture {Notes} in {Computer} {Science}},
	title = {A game theoretic analysis of the twitter follow-unfollow mechanism},
	volume = {11199},
	isbn = {978-3-030-01554-1},
	url = {http://link.springer.com/10.1007/978-3-030-01554-1_15},
	doi = {10.1007/978-3-030-01554-1_15},
	abstract = {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\%0.76\%0.76{\textbackslash}\% and 0.86\%0.86\%0.86{\textbackslash}\%. 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.},
	language = {en},
	booktitle = {Decision and {Game} {Theory} for {Security}},
	publisher = {Springer International Publishing},
	author = {Chen, Jundong and Hossain, Md Shafaeat and Brust, Matthias R. and Johnson, Naomi},
	editor = {Bushnell, Linda and Poovendran, Radha and Başar, Tamer},
	year = {2018},
	doi = {10.1007/978-3-030-01554-1_15},
	note = {Citation Key Alias: chenGameTheoreticAnalysis2018, pop00231
tex.type: [object Object]},
	keywords = {Game theory, Machine learning, Social network, Twitter bot, Twitter classification, dept.csc},
	pages = {265--276}
}

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