Paper Title
Social Media Issues - The Evolution of Fake News and using Machine Learning Detection

Abstract
Abstract – Technology and social media networks have evolved. The spread of fake news online is a great concern. Fake news is false information deliberatelymisleading individuals which impacts society negatively. There are potential factors contributing individuals to share fake news. There is a large amount of content online and the speed at which it is being distributed is fast which creates a challenge for an effective system to be developed to detect fake news. Enhanced machine learning could be used to detect fake news. The study aims to develop an understanding of the evolution of fake news and machine learning detection over the past five years.The study followed a systematic literature review. The literature review was guided by a synthesised approach using a framework developed by previous researchers in 2010. Research articles were synthesized by altering and summarising existing literature to understand the research phenomenon and to answer the specific research questions. After the 2016 UK elections concerns were raised around the impact of fake news in South Africa.This study developed theory by exploring the phenomenon within a South African context or other developing countries.This research can guide policy practice and decision making on the sharing of fake news. The research study contributes to the body of literature, adding knowledge for future research. Keywords - Fake News in South Africa, Social Media, Machine Learning, Information Literacy, Information Seeking, FoMo, Online Trust.

Author - Rushaye Smith, Michael Kyobe

Published : Volume-9,Issue-8  ( Aug, 2022 )

	|		PDF	|	Viewed - 31	|	Published on 2022-11-30