Survey on clustering techniques in Twitter data

Abstract

Social networks and online news services are used by users to communicate and share messages. One such social network is Twitter. Earlier its messages were restricted to 140 characters, but from November 7, 2017 its limit was extended to 280 characters except Japanese, Korean and Chinese languages. Because of restricted characters used, it is famously called micro blogging. Mining twitter data has become popular, because it provides useful information which is being used in various fields. This paper highlights various clustering techniques that can be used in twitter data mining with advantages and limitation.