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.
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Lee, J., Lakkaraju, K. (2014). Predicting Social Ties in Massively Multiplayer Online Games. In: Kennedy, W.G., Agarwal, N., Yang, S.J. (eds) Social Computing, Behavioral-Cultural Modeling and Prediction. SBP 2014. Lecture Notes in Computer Science, vol 8393. Springer, Cham. https://doi.org/10.1007/978-3-319-05579-4_12
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DOI: https://doi.org/10.1007/978-3-319-05579-4_12
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-05578-7
Online ISBN: 978-3-319-05579-4
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