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Information and Disseminator Features Influences Online Negative Information Recognition and Dissemination by Fei Meng; Liqin Chen; Paola Herring; Jianliang Wei is a Computer Science article available to read on EtoBox.

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Negative information on the Internet is a sticky problem for pattern recognition, especially that factors which in°uence its dissemination pattern remain uncertain. Combined with the elaboration likelihood model, this paper analyzes the factors that a®ect the negative information dissemination and its correlation mechanism, subdivides the in°uencing factors into negative information and disseminator features, introduces the interest degree as the mediator variable, and de ̄nes 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 signi ̄cant impact on the negative information dissemination intention, with the path coe±cient of 0.74. The emotionality of negative information, as well as the activity and credibility of the disseminator have a signi ̄cant impact on the degree of interest, while the completeness and harmfulness of negative information have a negative e®ect on user interest. Based on this, we put forward two management enlightenments for a better cybersecurity environment. First, take more computing methods to ̄nd out the emotionality, exhaustivity and damageability of nega

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Author

Fei Meng; Liqin Chen; Paola Herring; Jianliang Wei

Publisher

World Scientific Pub Co Pte Ltd

Published

2023

Language

EN

Field

Computer Science (Physical Sciences)