User Behavior Pattern and Deeper Intention Analysis in Online Social Media

The Internet has witnessed a rapid growth since last decade, Along with that we have also witnessed the tremendous growth in the internet users, and that leads to an exceptional growth in the data generated by the users. The main reason behind this rapid growth in the internet users is social networking sites. Users spend hours of their time every day on social networking sites like- Facebook, YouTube, Twitter and so on. There, every action performed by the user on those websites is being recorded to provide them the better user experience. Apart from making the user experience better, we can use such data to provide certain services on time if we are able to predict the user intention well ahead. Hence, this paper addresses the problem of finding the user's deeper intention based on their past behaviour. In this paper we introduced two additional parameters, time and location in addition to the existing parameters used in the intention serialization algorithm. The proposed approach enriches the Intention Serialization algorithm.