Impact of influence analysis of social media fake news - a machine learning perspective

Abstract

Nowadays, fake news and fake user profiles spread across online communities, such as social media. This fake news is becoming more popular and influencing people's opinions, emotions, and behaviors due to information diffusion among social media users. Social media influence analysis becomes more prevalent in the activities of billions of users on a day-to-day basis. Sometimes this fake news is spread by posts using some fake user profile. This work predicts fake news in social media and fake profiles using machine learning algorithms. We calculate the influence study of this fake news by predicting the online user behavior analysis. The experimental study evaluates the effects of such news propagation on online users and uses simple prediction techniques. We analyze the influence of fake news on public psychological analysis by using machine learning techniques. The proposed system analyses various possible real and fake news indicators and implementation that correctly represent the classifications. The outcomes show that the influence score seems to be more efficient in determining actual essential factors.