Research Article: “False Information on Web and Social Media: A Survey”

The following article was recently made available on arXiv.
Title
False Information on Web and Social Media: A Survey
Authors
Srijan Kumar
Stanford University
Neil Shah
Carnegie Mellon University
Source
via arxiv
April 23, 2018.
Note

A previous version of this survey will appear in the book titled Social Media Analytics: Advances and Applications, by CRC Press in 2018.

Abstract

False information can be created and spread easily through the web and social media platforms, resulting in widespread real-world impact. Characterizing how false information proliferates on social platforms and why it succeeds in deceiving readers are critical to develop efficient detection algorithms and tools for early detection. A recent surge of research in this area has aimed to address the key issues using methods based on feature engineering, graph mining, and information modeling.
Majority of the research has primarily focused on two broad categories of false information: opinion-based (e.g., fake reviews), and fact-based (e.g., false news and hoaxes). Therefore, in this work, we present a comprehensive survey spanning diverse aspects of false information, namely (i) the actors involved in spreading false information, (ii) rationale behind successfully deceiving readers, (iii) quantifying the impact of false information, (iv) measuring its characteristics across different dimensions, and finally, (iv) algorithms developed to detect false information. In doing so, we create a unified framework to describe these recent methods and highlight a number of important directions for future research.

Direct to Full Text Article 
35 pages; PDF.

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