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Communication Dans Un Congrès Année : 2014

Clustering and Classification of Like-Minded People from Their Tweets

Résumé

Several challenges accompanied the growth of online social networks, such as grouping people with similar interest. Grouping like-minded people is of a high importance. Indeed, it leads to many applications like link prediction and friend or product suggestion, and explains various social phenomenon. In this paper, we present two methods of grouping like-minded people based on their textual posts. Compared to three baseline methods K-Means, LDA and the Scalable Multi-stage Clustering algorithm (SMSC), our algorithms achieves relative improvements on two corpora of tweets.
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Dates et versions

hal-01112778 , version 1 (03-02-2015)

Identifiants

  • HAL Id : hal-01112778 , version 1

Citer

Soufiene Jaffali, Salma Jamoussi, Ben Abdelmajid, Kamel Smaili. Clustering and Classification of Like-Minded People from Their Tweets. COOL-SNA Workshop on Connecting Online and Offline Social Network Analysis' of the IEEE International Conference on Data Mining (ICDM'14), Dec 2014, Shenzen, China. ⟨hal-01112778⟩
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