Personalizing Information Using Users’ Online Social Networks: A Case Study of CiteULike

Danielle Lee
Volume: 11, No: 1, Page: 1 ~ 21, Year: 2015
10.3745/JIPS.04.0014
Keywords: CiteULike, Homophily, Information Personalization, Online Social Networks, Social Network-based Recommendations
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Abstract
This paper aims to assess the feasibility of a new and less-focused type of online sociability (the watching network) as a useful information source for personalized recommendations. In this paper, we recommend scientific articles of interests by using the shared interests between target users and their watching connections. Our recommendations are based on one typical social bookmarking system, CiteULike. The watching network-based recommendations, which use a much smaller size of user data, produces suggestions that are as good as the conventional Collaborative Filtering technique. The results demonstrate that the watching network is a useful information source and a feasible foundation for information personalization. Furthermore, the watching network is substitutable for anonymous peers of the Collaborative Filtering recommendations. This study shows the expandability of social network-based recommendations to the new type of online social networks.

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Cite this article
IEEE Style
Danielle Lee, "Personalizing Information Using Users’ Online Social Networks: A Case Study of CiteULike," Journal of Information Processing Systems, vol. 11, no. 1, pp. 1~21, 2015. DOI: 10.3745/JIPS.04.0014.

ACM Style
Danielle Lee, "Personalizing Information Using Users’ Online Social Networks: A Case Study of CiteULike," Journal of Information Processing Systems, 11, 1, (2015), 1~21. DOI: 10.3745/JIPS.04.0014.