Website: ijetms.in Issue:5, Volume No.4, August-2020 DOI: 10.46647/ijetms.2020.v04i05.011 57 FRIEND RECOMMENDATION USING GRAPH MINING ON SOCIAL MEDIA Kosaraju Naren Kumar 1 , Kanakamedala Vineela 2 1 Student &Sathyabama University. 2 Assistant Professor & NRI Institute of Technology. 1 naren010898@gmail.com. 2 vineela.nriit@gmail.com. Abstract: Recommendation system is an important type of machine learning algorithm that provide precise suggestions to the users. Recommendation systems are used in innumerable types of areas such as generation of playlists, music and video services like Jio savaan, wynk, amazon prime music etc., and products recommendation for users in e-commerce applications and commercial applications. The recommendations that are provided by various types of applications increases the speed for identifying and makes easier to access the products that users are interested in. For each user, the recommendation system is capable of envisaging the future predilections on a set of items and recommend the top items. In several industries, recommendation systems are very useful as they generate huge amount of income and this type of industries can stand uniquely from competitors. Due to cumbersome number of items that each user can find in the web, the impact of recommendation system has been increased in the internet. Recommendation systems are used for custom-made navigation by getting huge amount of data particularly in social media domain for recommending friends. A recommendation system act as a subclass for the information filtering system that pursue to predict the rating. The similarity measures that are calculated in this research are Jaccard distance and Otsuka-Ochiai coefficient. The feature extractions that are used in this paper are Adar index, PageRank, Katz centrality, Hits score. Now a days many research people are implementing different types of algorithms in various domains for recommendation systems. Keywords:Adar Index, In-degree, Jaccard Distance, Katz Centrality, Out-degree, Social Network Recommendation system. I.INTRODUCTION The recommendation system is used to recommend the user based on their preferences. In recent times social media is enjoying a great deal of success with a million of users visiting many sites like Facebook, Twitter etc. for social networking. By using computational methods such as natural language processing, data mining machine learning etc., social recommendation system involves the investigation of collective intelligence of data from wikis, query locks, Q&A communities etc. The information that is very much interested by the users is suggested by the recommendation system by using information filtering techniques. Social recommendation system is a system that recommends the friends in social media applications such as the Facebook, Twitter, Instagram etc. Over the last couple of years, for social media personalized recommendation systems are came into existence. For example, StumbleUpon is a customized recommendation system which suggests web pages for