RECENT INFLUENCE DISCOVERY IN SOCIAL MEDIA

Abstract

Everlasting information flow in social networks influences the members of these social networks. Entities in these networks influences other entities in the network by performing various activities. For example in Twitter network, entities influence other entities' activities when they tweet on different topics. Studies had been done to determine the top influencers in the whole network, but none considers a user's perspective as of what entities by which a user is influenced. We have developed an algorithm that considers a user's perspective to determine influence on that user. Other metric that has not been explored is the timeliness of the influence. Influence on a user changes rapidly, so we have developed an algorithm to determine the recent influence of a user considering his perspective