Proceedings of the 2022 2nd International Conference on Education, Information Management and Service Science (EIMSS 2022)

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Design and Implementation of Rumor Refuting and Accountability System Based on Deep Learning and Graphic Database

Authors
Jingrong Wang1, Haori Lu1, Yutong Li1, Jiazhen Song2, Peng Nie3, *
1College of Cyber Science, Nankai University, Tianjin, 300350, China
2College of Computer Science, Nankai University, Tianjin, 300350, China
3College of Cyber Science and Tianjin Key Laboratory of Network and Data Security Technology, Nankai University, Tianjin, 300350, China
*Corresponding author. Email: niepeng@nankai.edu.cn
Corresponding Author
Peng Nie
Available Online 12 December 2022.
DOI
10.2991/978-94-6463-024-4_34How to use a DOI?
Keywords
Deep learning; Graphic databases; Refuting rumors; Accountability system
Abstract

With the popularity of social networks, online rumors are increasing day by day. Internet rumors are harmful, spread fast, and will cause great loss to personal interests and social interests. In order to suppress the spread of online rumors and hold those who spread rumors accountable, we designed and implemented a system to refute and hold those responsible for online rumors accountable. The system has two major functions. First, with the help of deep learning model, it can automatically detect whether the news reported by users is rumor or not, and push the correct news to all users who have browsed the wrong news, so as to suppress the rumor spread. Second, with the help of graphic database, the whole process of rumor generation and dissemination can be displayed in detail, thus providing strong evidence for relevant departments to investigate the responsibility of those who spread rumors.

Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the 2022 2nd International Conference on Education, Information Management and Service Science (EIMSS 2022)
Series
Atlantis Highlights in Computer Sciences
Publication Date
12 December 2022
ISBN
978-94-6463-024-4
ISSN
2589-4900
DOI
10.2991/978-94-6463-024-4_34How to use a DOI?
Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Jingrong Wang
AU  - Haori Lu
AU  - Yutong Li
AU  - Jiazhen Song
AU  - Peng Nie
PY  - 2022
DA  - 2022/12/12
TI  - Design and Implementation of Rumor Refuting and Accountability System Based on Deep Learning and Graphic Database
BT  - Proceedings of the 2022 2nd International Conference on Education, Information Management and Service Science (EIMSS 2022)
PB  - Atlantis Press
SP  - 322
EP  - 330
SN  - 2589-4900
UR  - https://doi.org/10.2991/978-94-6463-024-4_34
DO  - 10.2991/978-94-6463-024-4_34
ID  - Wang2022
ER  -