Mitigating popularity bias in Twitter- Recommending novel hashtags using pooled tweets

Twitter has grown as a popular microblogging site in the last decade. A tweet, is a small, crisp 140 characters-based text in Twitter. It lets people raise their opinions, convey ideas and to follow other events or people. Hashtags in the Twitter network allow spread of a particular idea, event and help in easy search in the voluminous amount of data. The hashtags used by twitter users may strengthen particular hashtag conversation leading to a number of tweets concerning the idea. Twitter-pooling phenomenon refers to collection of tweets based on hashtags or conversations. We use hashtag-based twitter pooling in this work.Recommender Systems (RSs) suggest user-oriented suggestions for items from a plethora of options available across the Internet. Recommendations may be generated keeping in view the other similar users or items across the recommendation environment. Research in recommendation for social networks has been worked upon lately. In this paper, we strive to suggest hashtags to be used by the twitter users. We propose a notion to recommend novel hashtags in Twitter to handle the prevalent challenge of popularity bias across RSs. The idea of novelty in hashtag recommendation has been utilized for this research motive.