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General Information

Prof. Pascal Lorenz
University of Haute Alsace, France
It is my honor to be the editor-in-chief of IJFCC. The journal publishes good papers in the field of future computer and communication. Hopefully, IJFCC will become a recognized journal among the readers in the filed of future computer and communication.

IJFCC 2020 Vol.9(3): 57-61 ISSN: 2010-3751
DOI: 10.18178/ijfcc.2020.9.3.566

Analysis of Association Degree Algorithm Based on Complex Network Public Opinion

Jing Luo and Guoqing Xu
Abstract—The network public opinion plays an irreplaceable role in today's society. The analysis and processing of data mining can effectively find out the sensitive network public opinion and prevent the intensification of social public opinion. In this paper, we propose an association degree algorithm between personal speech and user real name information in Chinese community. By defining the user's name, address, ID number, phone number, QQ number, e-mail, MSN and other information as keywords and setting different weights. The hot public opinion phrases in user comments are extracted, the word frequency is counted, the text semantic similarity classification model is constructed, the semantic tree of unknown text is automatically constructed, the semantic relevance based on the topic is calculated, and the relevance between the public opinion topic and the specified user information is obtained. The algorithm in this paper uses Chinese segmentation index technology and common algorithms of text de duplication technology. From the technical feasibility, economic feasibility and other aspects of the feasibility analysis; from the system response speed, scalability and security three main levels of the system function requirements analysis. The results show that the system design meets the requirements and improves the accuracy of online public opinion text collection and emotional analysis.

Index Terms—Application in classification, big-data analysis, clustering, FP-growth algorithms

Jing Luo is with the Wuhan Institute of Technology, China (e-amil: 971672513@qq.com).


Cite: Jing Luo and Guoqing Xu, "Analysis of Association Degree Algorithm Based on Complex Network Public Opinion," International Journal of Future Computer and Communication vol. 9, no. 3, pp. 57-61, 2020.

Copyright © 2020 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

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