Abstract
Social networking systems originally emerged as tools for keeping up with the daily lives of friends and strangers. They have established themselves as valuable resources and means to satisfy information needs. The challenge with information seeking through social networks is that their immense success and popularity is also a weakness. The data deluge facing users has surpassed comfortably managed levels and can impact on the quality and relevance of the information consumed. We developed a personalized model for predicting the relevance of news feed items, in order to facilitate personalized feeds. Results of a live analysis show that our approach successfully identifies and promotes relevant feed items, with the knock-on effects of increasing interaction between users and the contribution of user generated content.
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Berkovsky, S., Freyne, J., Smith, G. (2012). Personalized Network Updates: Increasing Social Interactions and Contributions in Social Networks. In: Masthoff, J., Mobasher, B., Desmarais, M.C., Nkambou, R. (eds) User Modeling, Adaptation, and Personalization. UMAP 2012. Lecture Notes in Computer Science, vol 7379. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31454-4_1
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DOI: https://doi.org/10.1007/978-3-642-31454-4_1
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