A Survey of Fake News: Fundamental Theories, Detection Methods, and Opportunities

TL;DR

This survey comprehensively reviews fake news detection methods, fundamental theories, and future research opportunities across multiple disciplines to improve detection accuracy and explainability.

Contribution

It provides an interdisciplinary overview of fake news detection techniques and highlights fundamental theories to guide future research efforts.

Findings

Identifies four key perspectives for fake news detection

Highlights fundamental theories across disciplines

Suggests future research directions for explainable detection

Abstract

The explosive growth in fake news and its erosion to democracy, justice, and public trust has increased the demand for fake news detection and intervention. This survey reviews and evaluates methods that can detect fake news from four perspectives: (1) the false knowledge it carries, (2) its writing style, (3) its propagation patterns, and (4) the credibility of its source. The survey also highlights some potential research tasks based on the review. In particular, we identify and detail related fundamental theories across various disciplines to encourage interdisciplinary research on fake news. We hope this survey can facilitate collaborative efforts among experts in computer and information sciences, social sciences, political science, and journalism to research fake news, where such efforts can lead to fake news detection that is not only efficient but more importantly, explainable.