Proceedings of the 2020 4th International Seminar on Education, Management and Social Sciences (ISEMSS 2020)

The Text Mining Application of “Intelligent Government Affairs”

Authors
Huang Runchen, Wang Benhui, Yang Wenjue
Corresponding Author
Huang Runchen
Available Online 28 August 2020.
DOI
10.2991/assehr.k.200826.274How to use a DOI?
Keywords
TF-IDF, F-score, correlation coefficient, significance level
Abstract

In recent years, with WeChat, microblog, mayor’s mailbox and other network political platforms continue to become an important channel for the government to understand public opinion, gather people’s wisdom, and condense people’s morale. The number of texts of various data has increased sharply. The traditional manual data processing methods have appeared problems such as low efficiency and tedious work. Therefore, it is of great significance to use text analysis and data mining methods to deal with mass messages and improve the efficiency of government. In this paper, based on the records of people’s political questions, through some algorithms and some mathematical tools, this paper analyzes the hot areas and hot issues, and gives a set of evaluation scheme for the quality of the reply from the perspective of relevance, integrity and interpretability. Finally, the reliability of the score is verified by various formulas, which shows that the model has high accuracy.

Copyright
© 2020, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2020 4th International Seminar on Education, Management and Social Sciences (ISEMSS 2020)
Series
Advances in Social Science, Education and Humanities Research
Publication Date
28 August 2020
ISBN
10.2991/assehr.k.200826.274
ISSN
2352-5398
DOI
10.2991/assehr.k.200826.274How to use a DOI?
Copyright
© 2020, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Huang Runchen
AU  - Wang Benhui
AU  - Yang Wenjue
PY  - 2020
DA  - 2020/08/28
TI  - The Text Mining Application of “Intelligent Government Affairs”
BT  - Proceedings of the 2020 4th International Seminar on Education, Management and Social Sciences (ISEMSS 2020)
PB  - Atlantis Press
SP  - 1328
EP  - 1332
SN  - 2352-5398
UR  - https://doi.org/10.2991/assehr.k.200826.274
DO  - 10.2991/assehr.k.200826.274
ID  - Runchen2020
ER  -