Internet Public Opinion Recognition and Tracking Based on Web Mining

Article Preview

Abstract:

Recent years have observed the frequent occurrences of grave negative events. Along with the application and evolvement of Internet and new media, enthusiasms in distribution and discussing public opinion events have heightened. Internet public opinion research has thus become one of the research priorities of scholars in recent years. Internet public opinion research places heavy premium upon the emergence, evolvement, influencing factors and other aspects of public opinion. With rapid development and deepen evolution of internet public opinion in the internet, a variety of new methods occur on network. As the internet public opinion possesses the features of various topic, complex content and large amount data, the paper constructs an internet public opinion recognition and tracking based on web mining. Then the framework of the internet public opinion recognition and tracking system is presented. At last, it puts forward the whole workflow of the system to process the internet public opinion.

You might also be interested in these eBooks

Info:

Periodical:

Advanced Materials Research (Volumes 989-994)

Pages:

4909-4912

Citation:

Online since:

July 2014

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2014 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

* - Corresponding Author

[1] Zeng J, Zhang S, Wu C, et al. Predictive model for internet public opinion[C]/Fuzzy Systems and Knowledge Discovery, 2007. FSKD 2007. Fourth International Conference on. IEEE, 2007, 3: 7-11.

DOI: 10.1109/fskd.2007.453

Google Scholar

[2] Songjie Gong, Learning User Interest Model for Content-based Filtering in Personalized Recommendation System, International Journal of Digital Content Technology and its Applications, Vol. 6, No. 11, p.155 ~ 162, (2012).

DOI: 10.4156/jdcta.vol6.issue11.20

Google Scholar

[3] Guan Q, Ye S, Yao G, et al. Research and design of internet public opinion analysis system[C]/Services Science, Management and Engineering, 2009. SSME'09. IITA International Conference on. IEEE, 2009: 173-177.

DOI: 10.1109/ssme.2009.62

Google Scholar

[4] Songjie Gong, A Collaborative Filtering Recommendation Algorithm Based on Trust Network and Trust Factor, Journal of Convergence Information Technology, Vol. 8, No. 5, p.1111 ~ 1118, 2013. 03.

DOI: 10.4156/jcit.vol8.issue5.129

Google Scholar

[5] CUI W, ZENG R, WANG G. Bibliometric Analysis of Internet Public Opinion in China [J][J]. Information Science, 2011, 1: 131-135.

Google Scholar

[6] Songjie Gong, Research on Attack on Collaborative Filtering Recommendation Systems, AISS: Advances in Information Sciences and Service Sciences, Vol. 5, No. 10, p.938 ~ 946, 2013. 05.

DOI: 10.4156/aiss.vol5.issue10.110

Google Scholar

[7] Mingyi G, Renwei Z. A Research on Social Network Information Distribution Pattern With Internet Public Opinion Formation [J][J]. Journalism & Communication, 2009, 5(4): 72-78.

Google Scholar