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Information and Disseminator Features Influences Online Negative Information Recognition and Dissemination.

Authors :
Meng, Fei
Chen, Liqin
Herring, Paola
Wei, Jianliang
Source :
International Journal of Pattern Recognition & Artificial Intelligence; Mar2023, Vol. 37 Issue 3, p1-20, 20p
Publication Year :
2023

Abstract

Negative information on the Internet is a sticky problem for pattern recognition, especially that factors which influence its dissemination pattern remain uncertain. Combined with the elaboration likelihood model, this paper analyzes the factors that affect the negative information dissemination and its correlation mechanism, subdivides the influencing factors into negative information and disseminator features, introduces the interest degree as the mediator variable, and defines the identity of the receiver as the moderator variable. Through the questionnaire survey and data analysis by SPSS, we found that interest degree has a significant impact on the negative information dissemination intention, with the path coefficient of 0.74. The emotionality of negative information, as well as the activity and credibility of the disseminator have a significant impact on the degree of interest, while the completeness and harmfulness of negative information have a negative effect on user interest. Based on this, we put forward two management enlightenments for a better cybersecurity environment. First, take more computing methods to find out the emotionality, exhaustivity and damageability of negative information; second, use forms of artificial intelligence to respond to negative information in a timely manner and enhance the credibility of antagonistic information. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
02180014
Volume :
37
Issue :
3
Database :
Complementary Index
Journal :
International Journal of Pattern Recognition & Artificial Intelligence
Publication Type :
Academic Journal
Accession number :
162594935
Full Text :
https://doi.org/10.1142/S0218001423500052