Task-Oriented Social Ego Network Generation via Dynamic Collaborator Selection

Social networks are social structures derived from general human societies based upon certain scope or relationships. People in social networks, rather than behaving randomly, are highly organized and cooperative. To study evolutions of social networks, existing random graph theories only provide global views on network evolutions. Nevertheless, the evolutions of a social network should be examined from a local point of view. That is we can claim that someone's social network has evolved, if and only if the network is indeed evolved from the person's perspective. Hence, in this paper, we introduce the concept of social ego network. We propose two dynamic collaborator selection methods for the Task-Oriented Social Ego Network Generation process, which is believed to be the key process of social ego network evolution. We also conduct experimental simulations for our proposed methods.