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Initial spreaders in online social networks

The advent of social media has generated tremendous interest in ways that organizations or companies use social networks to maximize information or product adoption by users. In this paper, we are interested in finding powerful information initial spreaders. We utilize a ubiquitous feature of social networks, namely the existence of communities (i.e., tight-knit groups of nodes), and design a community-based distributed algorithm to find initial spreaders which maximize information spreading. In addition to the rigorous analysis, we also demonstrate our result with experiments over real network topologies.