Abstract: Twitter, Facebook are few prominent Social media platforms to share information. On the other hand, the Internet being an open and free source forum is attracted by news media which have utilized online platforms to publish news articles. An attempt to examine the trending topics in Twitter, Facebook and News Media is the focus of our study. In this paper, we propose a Recommendation System based on Soci- Similarity based on trending topics shared by people in different social media. Compare the effect of trending topics in Media Focus and User Interaction of people. On the predefined days we examine the trending topics of similarity by applying K – Means Clustering to cluster the topics. And we further measure Media Focus and User Interaction using the performance metrics such as Precision, Recall and F1-Score.

Keywords: Recommendation System, Similarity, K-Means Clustering.

PDF | DOI: 10.17148/IJARCCE.2020.9804

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