The Influence of the Social Media Recommendation System Against Polarization in the Views of User Politics: Experiments on Social Media Newsfeed on Social Media Users

The background of this research is based on 2019 election issues that spread massively in social media. From these issues comes the polarization and divides into two opposing sides. However, users are basically not presented with balanced information as a result of the recommendation system on social media. This research is expected to enrich the study of social media impact, especially on study of recommendation system with context in Indonesia. This thesis examines the recommendation system designed by social media operators tends to be uniform or aligned with the user's political views only. The phenomenon is The Filter Bubbles where the information circulating on our social media is filtered only in accordance with the user's own views. Polarization becomes an effect that can be influenced by the recommendation system because the acceptance of information from the user after going through a personalized curation system raises uniform news. This research uses quantitative approach with experiment method. The results of this study indicate that the recommendation system makes the polarization position of users more extreme. This is marked by increasingly persistent opinions and political views held by previous users.