Big Social Network Mining for "Following" Patterns

Abstract

Many social networking sites such as Facebook and Twitter have been used for sharing knowledge and information among social entities. Social entities in these social networks are often linked by some interdependency such as friendship or following relationships. Amounts of high volumes of high-value data can be easily collected and generated in these social networking sites. As the size of the social network keeps increasing in the current era of big data, there are many real-life situations in which a social entity wants to find those frequently followed groups of social entities from these big data so that he can follow the same groups. In this paper, we present a big data mining algorithm to discover following patterns from these big social network data. Evaluation results show the efficiency and practicality of our algorithm in big social network mining for the following patterns.