Journal Article: “Combating Fake News: A Survey on Identification and Mitigation Technique”

The following article was recently shared on arXiv. It’s an open access version of an article that was published in ACM Trans. Intell. Syst. Technol. 37, 4, Article 111 (August 2018).

Title

Combating Fake News: A Survey on Identification and Mitigation Technique

Authors

Karishma Sharma
University of Southern California

Feng Qian
University of Southern California

He Jiang
University of Southern California

Natali Ruchansky
University of Southern California

Ming Zhang
Peking University

Yan Liu
University of Southern California

Source

via arXiv

Abstract

The proliferation of fake news on social media has opened up new directions of research for timely identification and containment of fake news, and mitigation of its widespread impact on public opinion. While much of the earlier research was focused on identification of fake news based on its contents or by exploiting users’ engagements with the news on social media, there has been a rising interest in proactive intervention strategies to counter the spread of misinformation and its impact on society. In this survey, we describe the modern-day problem of fake news and, in particular, highlight the technical challenges associated with it. We discuss existing methods and techniques applicable to both identification and mitigation, with a focus on the significant advances in each method and their advantages and limitations. In addition, research has often been limited by the quality of existing datasets and their specific application contexts. To alleviate this problem, we comprehensively compile and summarize characteristic features of available datasets. Furthermore, we outline new directions of research to facilitate future development of effective and interdisciplinary solutions.

Direct to Full Text Article
41 pages; PDF.

Filed under: Data Files, News, Open Access