Classification of followee recommendation techniques in Twitter

Abstract

Recommender system aims to predict the user preference for a given item. These systems have been widely used to recommend movies, music, news, books, products and even people. Twitter has become an interesting source of research activity due to the large amount of data generated everyday by its users in order to overcome the information overload problem. There are various aspects of Twitter that can be recommended including Followee, Tweet, Hashtag and URL Recommendation. Recommendation system can be used to find the useful people from large number of users connected and interacting in Twitter network. This paper aims to study and classify the different techniques of followee recommendation that exists so far. Along with, it also highlights the different research directions in the existing recommendation techniques described.