کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
523110 868259 2012 17 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Adding community and dynamic to topic models
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر نرم افزارهای علوم کامپیوتر
پیش نمایش صفحه اول مقاله
Adding community and dynamic to topic models
چکیده انگلیسی

The detection of communities in large social networks is receiving increasing attention in a variety of research areas. Most existing community detection approaches focus on the topology of social connections (e.g., coauthor, citation, and social conversation) without considering their topic and dynamic features. In this paper, we propose two models to detect communities by considering both topic and dynamic features. First, the Community Topic Model (CTM) can identify communities sharing similar topics. Second, the Dynamic CTM (DCTM) can capture the dynamic features of communities and topics based on the Bernoulli distribution that leverages the temporal continuity between consecutive timestamps. Both models were tested on two datasets: ArnetMiner and Twitter. Experiments show that communities with similar topics can be detected and the co-evolution of communities and topics can be observed by these two models, which allow us to better understand the dynamic features of social networks and make improved personalized recommendations.


► We detected communities based on topical similarity.
► We modeled the dynamic change of communities.
► We evaluated our models to academic and social network dataset.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Informetrics - Volume 6, Issue 2, April 2012, Pages 237–253
نویسندگان
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