中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
Identifying and Analyzing Popular Phrases Multi-Dimensionally in Social Media Data

文献类型:期刊论文

作者Zhongying Zhao; Chao Li; Yong Zhang; Joshua Zhexue Huang; Jun Luo; Shengzhong Feng; Jianping Fan
刊名International Journal of Data Warehousing and Mining
出版日期2015
英文摘要With the success of social media, social network analysis has become a very hot research topic and attracted much attention in the last decade. Most studies focus on analyzing the whole network from the perspective of topology or contents. However, there is still no systematic model proposed for multi-dimensional analysis on big social media data. Furthermore, little work has been done on identifying emerging new popular phrases and analyzing them multi-dimensionally. In this paper, the authors first propose an interactive systematic framework. In order to detect the emerging new popular phrases effectively and efficiently, they present an N-Pat Tree model and give some filtering mechanisms. They also propose an algorithm to find and analyze new popular phrases multi-dimensionally. The experiments on one-year Tencent-Microblogs data have demonstrated the effectiveness of their work and shown many meaningful results.
收录类别SCI
原文出处http://dl.acm.org/citation.cfm?id=2790932
语种英语
源URL[http://ir.siat.ac.cn:8080/handle/172644/6847]  
专题深圳先进技术研究院_数字所
作者单位International Journal of Data Warehousing and Mining
推荐引用方式
GB/T 7714
Zhongying Zhao,Chao Li,Yong Zhang,et al. Identifying and Analyzing Popular Phrases Multi-Dimensionally in Social Media Data[J]. International Journal of Data Warehousing and Mining,2015.
APA Zhongying Zhao.,Chao Li.,Yong Zhang.,Joshua Zhexue Huang.,Jun Luo.,...&Jianping Fan.(2015).Identifying and Analyzing Popular Phrases Multi-Dimensionally in Social Media Data.International Journal of Data Warehousing and Mining.
MLA Zhongying Zhao,et al."Identifying and Analyzing Popular Phrases Multi-Dimensionally in Social Media Data".International Journal of Data Warehousing and Mining (2015).

入库方式: OAI收割

来源:深圳先进技术研究院

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