Twitter User Clustering Based on Their Preferences and the Louvain Algorithm

被引：17

作者：

Lopez Sanchez, Daniel ^{[1
]}

Revuelta, Jorge ^{[1
]}

De la Prieta, Fernando ^{[1
]}

Gil-Gonzalez, Ana B. ^{[1
]}

Cach Dang ^{[2
]}

机构：

[1] Univ Salamanca, Dept Comp Sci & Automat Control, Plaza Merced S-N, Salamanca 37007, Spain

[2] HoChiMinh City Univ Transport UT HCMC, Ho Chi Minh City, Vietnam

来源：

TRENDS IN PRACTICAL APPLICATIONS OF SCALABLE MULTI-AGENT SYSTEMS, THE PAAMS COLLECTION | 2016年 / 473卷

关键词：

Clustering; Data mining; Community detection; Visualization; SOCIAL MEDIA; INFORMATION;

D O I：

10.1007/978-3-319-40159-1_29

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this paper, a novel agent-based platform for Twitter user clustering is proposed. We describe how our system tracks the activity for a given topic in the social network and how to detect communities of users with similar political preferences by means of the Louvain Modularity. The quality of this clustering method is evaluated against a subset of human-labeled user profiles. Finally, we propose combining community detection with a force-directed graph algorithm to produce a visual representation of the political communities.

引用

页码：349 / 356

页数：8

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