Proceedings of the 2018 International Conference on Mathematics, Modelling, Simulation and Algorithms (MMSA 2018)

Research on Hot Words Mining Algorithm of University Network Public Sentiment

Authors
Liang Hu, Hongmei Yu
Corresponding Author
Liang Hu
Available Online March 2018.
DOI
10.2991/mmsa-18.2018.43How to use a DOI?
Keywords
network public opinion; hot words; data mining; university
Abstract

Hot words are the topic of concern of the netizens, which can help the management department to monitor the public opinion of the network. Due to the large degree of freedom, irregular syntax and immediacy of data, it is difficult for data engine to grasp text hotspots accurately through traditional text analysis. This paper deals with the text features of a time span, and determines whether it is a hot word by adding the time information of the span. Through experiments, the hot words excavated correspond to the corresponding hot events. This shows that the method proposed in this paper has a good effect and can be further studied.

Copyright
© 2018, 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 2018 International Conference on Mathematics, Modelling, Simulation and Algorithms (MMSA 2018)
Series
Advances in Intelligent Systems Research
Publication Date
March 2018
ISBN
978-94-6252-499-6
ISSN
1951-6851
DOI
10.2991/mmsa-18.2018.43How to use a DOI?
Copyright
© 2018, 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  - Liang Hu
AU  - Hongmei Yu
PY  - 2018/03
DA  - 2018/03
TI  - Research on Hot Words Mining Algorithm of University Network Public Sentiment
BT  - Proceedings of the 2018 International Conference on Mathematics, Modelling, Simulation and Algorithms (MMSA 2018)
PB  - Atlantis Press
SP  - 195
EP  - 197
SN  - 1951-6851
UR  - https://doi.org/10.2991/mmsa-18.2018.43
DO  - 10.2991/mmsa-18.2018.43
ID  - Hu2018/03
ER  -