Abstract
In this paper, we present an overlapping microblog community detecting algorithm using a new partition criterion. The new partition criterion considers the explicit and implicit interest of users, together with the user’s attention and practical application. Users containing certain tag in the whole community are extracted as a temporary group and the quality value is calculated under the current partition. The most appropriate core tag is selected and the corresponding group is then updated until certain requirements are satisfied. The community detected by this algorithm share common core tags and the partition results can be revised. Experimental results show that the method is effective and has practical significance.
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Acknowledgement
The authors would also like to thank the anonymous referees for their valuable comments and helpful suggestions. The work is supported by the National Natural Science Foundation of China (No. 61762078, 61363058, 61762079) and Guangxi Key Laboratory of Trusted Software (No. kx201705).
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Ma, H., Xie, M., Wei, J., He, T. (2018). An Overlapping Microblog Community Detection Method Using New Partition Criterion. In: Liu, W., Giunchiglia, F., Yang, B. (eds) Knowledge Science, Engineering and Management. KSEM 2018. Lecture Notes in Computer Science(), vol 11062. Springer, Cham. https://doi.org/10.1007/978-3-319-99247-1_28
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DOI: https://doi.org/10.1007/978-3-319-99247-1_28
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