Machine Learning Approach to Classification of Online Users By Exploiting Information Seeking Behavior

With the exponential growth of digital content, the internet has become a vast repository of unstructured and continuous data originating from diverse sources. Advanced algorithms are increasingly employed to deliver relevant information based on a user’s intent. Online user behaviour involves various actions such as searching, sharing, and verifying information; however, a holistic analysis of these behaviours remains relatively unexplored. This research presents a machine learning-based approach to classify users according to their intent, derived from their online activities across three key dimensions: search, share, and verification behaviours. A comprehensive dataset was collected through questionnaires involving participants of varying age groups, occupations, and genders.