Abstract
In order to utilize effectively explicit user relationship and implicit topic relations for the detection of micro-blog user interest communities, a micro-blog user interest community detection approach is proposed. First, we analyze the follow relationship between the users to construct the user follow-ship network. Second, we construct the user interest feature vectors based on the concept of feature mapping to build a user-tag based interest relationship network. Third, we propose to build a guided user interest topic model and construct a topic-based interest relationship network. Finally, we integrate the above-mentioned three kinds of relationship network to construct a micro-blog user interest relationship network. Meanwhile, we propose a micro-blog user interest community detection algorithm based on the contribution of the neighboring nodes. The experiment result turns out that good effect has been achieved through our approach.
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Acknowledge
This paper is supported by the China National Nature Science Foundation (No.61175068, 61472168, 61163004), and The Key Project of Yunnan Nature Science Foundation (No.2013FA130). Corresponding author is Zhengtao Yu, E-mail ztyu@hotmail.com.
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Qin, Y., Yu, Z., Wang, Y., Gao, S., Shi, L. (2015). Approaches to Detect Micro-Blog User Interest Communities Through the Integration of Explicit User Relationship and Implicit Topic Relations. In: Zhang, X., Sun, M., Wang, Z., Huang, X. (eds) Social Media Processing. SMP 2015. Communications in Computer and Information Science, vol 568. Springer, Singapore. https://doi.org/10.1007/978-981-10-0080-5_9
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DOI: https://doi.org/10.1007/978-981-10-0080-5_9
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