Abstract
This paper examines an application for finding pertinent friends (followees) on Twitter. Whilst Twitter provides a great basis for receiving information, we believe a potential downfall lies in the lack of an effective way in which users of Twitter can find other Twitter users to follow. We apply several recommendation techniques to build a followee recommender for Twitter. We evaluate a variety of different recommendation strategies, using real-user data, to demonstrate the potential for this recommender system to correctly identify and promote interesting users who are worth following.
This work is supported by Science Foundation Ireland under grant 07/CE/I1147 and by Amdocs Inc.
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References
Chen, J., Geyer, W., Dugan, C., Muller, M., Guy, I.: Make new friends, but keep the old: recommending people on social networking sites. In: Proceedings of the 27th International Conference on Human Factors in Computing Systems, CHI 2009, pp. 201–210. ACM, New York (2009)
Guy, I., Ronen, I., Wilcox, E.: Do you know?: recommending people to invite into your social network. In: Proceedings of the 13th International Conference on Intelligent User Interfaces, IUI 2009, pp. 77–86. ACM, New York (2009)
Hannon, J., Bennett, M., Smyth, B.: Recommending twitter users to follow using content and collaborative filtering approaches. In: Proceedings of the Fourth ACM Conference on Recommender Systems, RecSys 2010, pp. 199–206. ACM, New York (2010)
Konstan, J.A., Miller, B.N., Maltz, D., Herlocker, J.L., Gordon, L.R., Riedl, J.: Grouplens: applying collaborative filtering to usenet news. Commun. ACM 40, 77–87 (1997)
Pazzani, M.J., Billsus, D.: Content-based recommendation systems. In: Brusilovsky, P., Kobsa, A., Nejdl, W. (eds.) Adaptive Web 2007. LNCS, vol. 4321, pp. 325–341. Springer, Heidelberg (2007)
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Hannon, J., McCarthy, K., Smyth, B. (2011). Finding Useful Users on Twitter: Twittomender the Followee Recommender. In: Clough, P., et al. Advances in Information Retrieval. ECIR 2011. Lecture Notes in Computer Science, vol 6611. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-20161-5_94
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DOI: https://doi.org/10.1007/978-3-642-20161-5_94
Publisher Name: Springer, Berlin, Heidelberg
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