Social Networks have undergone a dramatic growth and influenced everyone’s life in recent years. People share everything from daily life stories to the latest local and global news and events using social media. This rich and continuous flow of usergenerated content has received significant attention from many organizations and researchers and is increasingly becoming a primary source for social and marketing researches to name a few. Accordingly, a great number of works have been conducted to extract valuable information from different platforms. However, there are no specific studies that focus on categorizing social media users based on the texts they share about a specific event. Given that the identification of online users with common interest in a particular event can help event organizers to attract more visitors to future similar events; This work study concentrates on examining the similarity between such users from the aspect of textual published contents. In this work different approaches have been proposed and various experiments have been carried out to support an explanation concerning this notion. We take a systematic approach to accomplish this objective by applying topic modeling techniques, using statistical and data mining algorithms, combined with information visualization.
Please cite our paper "Analysis of online user behaviour for art and culture events" if you use the material.