Fake news is playing an increasingly dominant role in spreading misinformation by influencing people’s perceptions or knowledge to distort their awareness and decision-making. The growth of social media and online forums has spurred the spread of fake news causing it to easily blend with truthful information. This study provides a novel text analytics–driven approach to fake news detection for reducing the risks posed by fake news consumption. We first describe the framework for the proposed approach and the underlying analytical model including the implementation details and validation based on a corpus of news data. We collect legitimate and fake news, which is transformed from a document based corpus into a topic and event–based representation. Fake news detection is performed using a two-layered approach, which is comprised of detecting fake topics and fake events. The efficacy of the proposed approach is demonstrated through the implementation and validation of a novel FakE News Detection (FEND) system. The proposed approach achieves 92.49% classification accuracy and 94.16% recall based on the specified threshold value of 0.6.

Introduction

Fake news can be defined “as the online publication of intentionally or knowingly false statements of fact (Klein & Wueller, 2017).” In essence, the focus is on articles or messages posted online with the anticipation of the message going “viral”. Fake news thrives on the false rumors, hoaxes, sensationalism, and scandal resulting from the dissemination of news articles through social media (Fisher, 2014). While intentional harm is debated, various incentives, – such as monetary, social, and political benefits – often drive the fake news spread. Recent proliferation in the use of social media as a vehicle for spreading fake news has significantly raised the risks imposed on individuals as well as organizations by the spread of misinformation (false information). For example, social platforms are frequently used to spread fake news via modifying authentic news or making fabricated news. Very recently, Berners-Lee, the inventor of the World Wide Web, claimed that fake news has been one of the most disturbing Internet trends that have to be resolved (Swartz, 2017). It is challenging, if not futile, to detect deceptive news due to the diversity and disguise of deceptions. Fake news may cause adverse influence coupled with damages. It influences an individual’s decision-making and distorts one’s perceptions about the real events by altering the information feeds that are utilized for news consumption. At the organizational level, the impact is more adverse as it poses risk to their brand names and can potentially affect on the consumption of their product or services (Gross, 2017).