Users of Online Social Network (OSN) generate their own post by using texts, images, videos and resources like emojis, stickers etc., Among the different types of posts, the text content can easily be interpreted by other and exposes the full thoughts of a user towards a topic. This paper attempts to group similar users, who produced the same text posts towards a set of pre-defined topics. The similarity among users with their posts is calculated with the aid of linear Support Vector Machine (LinearSVM) classifier and the performance is evaluated.

OSN, Similar Users, LinearSVM, Text Classification, text posts, tf-idf vectorizer

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