Gayani Tennakoon

    Research interests

    Frequent pattern mining, social network mining, Hierarchy mining

    Research overview

    The immense popularity of social media creates a great opportunity for businesses, citizens, politicians and other services to reach the society easily. Because of the viral of “word of mouth effect”, social media is being used as an effective medium for marketing products and services, political campaigning and spreading awareness of disastrous events or incidents. However, the biggest challenge is identifying the initial set of users to maximise the dissemination of information. This problem has attracted a great attention from the social network mining research community. With ever growing networks, the problem remains unsolved and there is an increasing demand for effective and scalable solutions. Hierarchical interaction patterns of users in the network reflect the information flow as well as categorise prominent users into different influence levels. In this research, we introduce a novel approach to identify influential users based on hierarchies derived from frequent patterns of activities amongst the network users.