UGGreedy: Influence Maximization for User Group in Microblogging

We study a new influence maximization problem about how to find a seed set which can maximize the influence spread to a targeted user group in microblogging. To solve this problem, we propose a three stage User group greedy algorithm (UGGreedy) based on user attributes. To reduce network scale, we delete useless user nodes, and rank the rest of users based on user attributes to form a seed candidate set. We employ the seed candidate set to construct a simplified microblogging network graph. We propose a novel influence greedy algorithm based on influence accumulation spread to find the seed set. Experimental results show that UGGreedy can achieve remarkable efficiency on the influence maximization problem for user group in real microblogging networks.