社会媒体大数据分析研究综述_杜治娟1
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社会媒体大数据分析研究综述
*
杜治娟
+
，王 硕，王秋月，孟小峰
中国人民大学 信息学院，北京 100872
Survey on Social Media Big Data Analytics
DU Zhijuan
+
, WANG Shuo, WANG Qiuyue, MENG Xiaofeng
School of Information, Renmin University of China, Beijing 100872, China
+ Corresponding author: E-mail: nmg-duzhijuan@163.com
DU Zhijuan, WANG Shuo, WANG Qiuyue, et al. Survey on social media big data analytics Journal of Fron-
tiers of Computer Science and Technology, 2017, 11(1)：1-23.
Abstract: Social media, which consists of a large number of meaningful information, is an important way for people
to propagate information and express themselves. In recent years, it has become one of the most representative
sources of big data. Mining and analyzing the information has profound impact on social development. According to
the elements of social media, the current researches are divided into three categories, including analysis based on users,
analysis based on relationships and analysis based on interactive contents. Firstly, analyzing user-centered data from
user identification based multi-source heterogeneous network, community detection and user influence computing.
Secondly, analyzing user relationship strength calculation, information diffusion and influence maximization issues
based on interactive relationship-center. Thirdly, discussing feature extraction and selection, the topic or event mining,
multimedia data analysis and sentiment analysis issues based on user interactive content analyzing interactive
content-centric. Finally, this paper elaborates challenges of mining big data of social media and points out the future
work from information diffusion, influence computing, feature extraction and selection, news mining based on
Microblog, social media big data fusion and cross-lingual sentiment analysis 6 aspects.
* The National Natural Science Foundation of China under Grant Nos. 61379050, 61532010, 91224008, 61532016 (国家自然科学基
金); the National Key R&D Program of China under Grant Nos. 2016YFB1000602, 2016YFB1000603 (国家重点研发计划); the
Specialized Research Fund for the Doctoral Program of Higher Education of China under Grant No. 20130004130001 (高等学校博士
学科点专项科研基金); the Research Funds of Renmin University under Grant No. 11XNL010 (中国人民大学科学研究基金).
Received 2016-01, Accepted 2016-09.
CNKI网络优先出版: 2016-09-08, http://www.cnki.net/kcms/detail/11.5602.TP.20160908.1045.002.html
ISSN 1673-9418 CODEN JKYTA8
Journal of Frontiers of Computer Science and Technology
1673-9418/2017/11(01)-0001-23
doi: 10.3778/j.issn.1673-9418.1601037
E-mail: fcst@vip.163.com
http://www.ceaj.org
Tel: +86-10-89056056
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