Analysis design study for fake news identification and evaluation

Abstract

With the spread of the Internet and increasing amounts of self-proclaimed journalists, articles both true and inaccurate fill the web. These inaccurate articles, most commonly referred to as fake news, have proved to spread quickly and have immense social influence in society. Attempts to detect fake news articles through deep learning techniques and artificial intelligence prove the challenges in fake news detection. While detection techniques are still in development, there is not much research on how readers can discern fake news without technological aid. This paper addresses such limitations regarding the study of fake news detection and provide a detection model for readers. The model is based on logical steps built on detection cues mentioned in previous works. The appropriateness of the detection cues will be determined based on case studies. © 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.