Predicting social ties in massively multiplayer online games

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Abstract

Social media has allowed researchers to induce large social networks from easily accessible online data. However, relationships inferred from social media data may not always reflect the true underlying relationship. The main question of this work is: How does the public social network reflect the private social network? We begin to address this question by studying interactions between players in a Massively Multiplayer Online Game. We trained a number of classifiers to predict the social ties between players using data on public forum posts, private messages exchanged between players, and their relationship information. Results show that using public interaction knowledge significantly improves the prediction of social ties between two players and including a richer set of information on their relationship further improves this prediction. © 2014 Springer International Publishing Switzerland.

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APA

Lee, J., & Lakkaraju, K. (2014). Predicting social ties in massively multiplayer online games. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8393 LNCS, pp. 95–102). Springer Verlag. https://doi.org/10.1007/978-3-319-05579-4_12

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