@inproceedings{9463487699c643ac98d853975d4debda,
title = "Local community detection using social relations and topic features in social networks",
abstract = "Local community detection is an important research focus in social network analysis. Most existing methods share the intrinsic limitation of utilizing undirected and unweighted networks. In this paper, we propose a novel local community detection algorithm that fuses social relations and topic features in social networks. By defining a new social similarity, the proposed algorithm can effectively reveal the dynamic characteristics in social networks. In addition, the topic similarity is measured by Jensen–Shannon divergence, in which the topics are extracted from the user-generated content by topic models. Extensive experiments conducted on a real social network dataset demonstrate that our proposed algorithm outperforms methods based on social relations or topic features alone.",
keywords = "Local community detection, Social networks, Topic model",
author = "Chengcheng Xu and Huaping Zhang and Bingbing Lu and Songze Wu",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing AG 2017.; 16th China National Conference on Computational Linguistics, CCL 2017 and 5th International Symposium on Natural Language Processing Based on Naturally Annotated Big Data, NLP-NABD 2017 ; Conference date: 13-10-2017 Through 15-10-2017",
year = "2017",
doi = "10.1007/978-3-319-69005-6_31",
language = "English",
isbn = "9783319690049",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "371--383",
editor = "Maosong Sun and Baobao Chang and Xiaojie Wang and Deyi Xiong",
booktitle = "Chinese Computational Linguistics and Natural Language Processing Based on Naturally Annotated Big Data - 16th China National Conference, CCL 2017 and 5th International Symposium, NLP-NABD 2017, Proceedings",
address = "Germany",
}