Survey on Fake Information Generation, Dissemination and Detection

Abstract

The current booming development of the Internet has put the public in an era of information overload, in which false information is mixed and spread unscrupulously. This phenomenon has seriously disturbed the social network order. Thus, a substantial amount of research is beginning to be devoted to the effective management of fake information. We analyze the abnormal characteristics of fake information from its mechanism of generation and dissemination. In view of different exceptional features, we systematically sort out and evaluate the existing studies on false content detection. The commonly used public datasets, metrics, and performance are categorized and compared, hoping to provide a basis and guidance for related research. The study found that the current active social platforms show different novelty. The future direction should point to mining platform features of multi-domain sources, multi-data forms, and multi-language heterogeneity to provide more valuable clues for fake information.