Proceedings of the 2021 5th International Seminar on Education, Management and Social Sciences (ISEMSS 2021)

Research on early warning and control of public opinion based on Digital twin

Authors
Wang Kai, Gao Yang, He Jie
Corresponding Author
Wang Kai
Available Online 9 August 2021.
DOI
10.2991/assehr.k.210806.205How to use a DOI?
Keywords
public opinion warning, digital twinning, simulation deduction, intelligent decision-making
Abstract

This research focuses on how to use digital twinning technology to construct a simulation deduction system for public opinion warning in the face of public emergencies. It aims to improve the public opinion intelligent decision-making and response system, so as to enhance the ability of public opinion guidance, and to make a prediction, a decision and then a response in time on different aspects, like possibility of the public opinion, its size and time, even its development trend.

Copyright
© 2021, 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 2021 5th International Seminar on Education, Management and Social Sciences (ISEMSS 2021)
Series
Advances in Social Science, Education and Humanities Research
Publication Date
9 August 2021
ISBN
10.2991/assehr.k.210806.205
ISSN
2352-5398
DOI
10.2991/assehr.k.210806.205How to use a DOI?
Copyright
© 2021, 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  - Wang Kai
AU  - Gao Yang
AU  - He Jie
PY  - 2021
DA  - 2021/08/09
TI  - Research on early warning and control of public opinion based on Digital twin
BT  - Proceedings of the 2021 5th International Seminar on Education, Management and Social Sciences (ISEMSS 2021)
PB  - Atlantis Press
SP  - 1089
EP  - 1092
SN  - 2352-5398
UR  - https://doi.org/10.2991/assehr.k.210806.205
DO  - 10.2991/assehr.k.210806.205
ID  - Kai2021
ER  -