Artificial-intelligence-based disinformation discovery for social networks
Zhiying Zhu · 2025
In this era of rapid development of the Internet, disinformation, as a new public opinion phenomenon, is generated and disseminated through the Internet. The most important feature that distinguishes it from general disinformation is that the means of dissemination have changed from verbal transmission to the dissemination of textual information or multimedia information on the Internet. Its untruthful and deceptive information content has a great impact on society and people's lives. The wide range and fast speed of dissemination of false information makes it difficult to judge its dissemination channels and the scope of dissemination, and therefore it is impossible to detect false information in an effective and timely manner. In this paper, through the simulation of the BSS virtual community propagation model, the SIR model, we can discover its propagation mode in social networks. After getting a rough idea of the pattern of disinformation dissemination. From the perspective of artificial intelligence through the feature extraction model detection method and Web content filtering model method to effectively detect false information, to reduce the negative impact of false information dissemination on society.