Social networks have become a major communication channel for connecting people with varied interests beyond geographical boundaries. Among active users of social media who share common interests, there are certain users who influence the others in their decision making. This paper proposes a frame work to identify the trending topics of a given domain and the influence patterns that interrelates users with common interests on those topics. In addition to discovering trending topics of a given domain using K-Means clustering the framework estimates the influence scores of active users on their followers based on their response in the form of number of re tweets made by them on specific topics. The data set is collected from twitter on sports domain for a period of two months.
Volume 11 | Issue 2