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Recommending Who to Follow on Twitter Based on Tweet Contents and Social Connections

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DOI: 10.4236/sn.2013.24016    4,098 Downloads   7,586 Views   Citations

ABSTRACT

In this paper, we examine methods that can provide accurate results in a form of a recommender system within a social networking framework. The social networking site of choice is Twitter, due to its interesting social graph connections and content characteristics. We built a recommender system which recommends potential users to follow by analyzing their tweets using the CRM114 regex engine as a basis for content classification. The evaluation of the recommender system was based on a dataset generated from real Twitter users created in late 2009.

Conflicts of Interest

The authors declare no conflicts of interest.

Cite this paper

Tsourougianni, E. and Ampazis, N. (2013) Recommending Who to Follow on Twitter Based on Tweet Contents and Social Connections. Social Networking, 2, 165-173. doi: 10.4236/sn.2013.24016.

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