Titlebook: Data Science for Fake News; Surveys and Perspect Deepak P,Tanmoy Chakraborty,Santhosh Kumar G Book 2021 Springer Nature Switzerland AG 2021

不來(lái)

Suppository

On Unsupervised Methods for Fake News Detection limited work in unsupervised fake news detection in detail with a methodological focus, outlining their relative strengths and weaknesses. Lastly, we discuss various possible directions in unsupervised fake news detection and consider the challenges and opportunities in the space.

樹(shù)木中

彎曲的人

compassion

A Three-Dimensional Hybrid Grid: DRAGON Gridches and show how graph mining enables the whole task. We first introduce different kinds of information related to fake news, then divide the existing graph-based approaches into two scenarios, where various graphs and graph patterns are introduced to model the information on social media and characterize features of the fake news, respectively.

NATAL

構(gòu)成

使尷尬

Lyme-disease

PANEL

Graph Mining Meets Fake News Detectionches and show how graph mining enables the whole task. We first introduce different kinds of information related to fake news, then divide the existing graph-based approaches into two scenarios, where various graphs and graph patterns are introduced to model the information on social media and characterize features of the fake news, respectively.