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In this paper we propose GoDisco++, a gossip based approach for information dissemination in online social community networks. GoDiscoo++ uses local information available to nodes-that is information associated with a node and its neighbors. The algorithm exploits multiple relations which may exist between nodes, and applies social principles and behavior inspired decentralized mechanisms for targeted dissemination. The dissemination process works with the dual aims of (i) maximizing the spread among relevant nodes (high recall) and (ii) minimizing spamming among non-relevant nodes (high precision). Such a designed dissemination scheme can have interesting applications like probabilistic publish/subscribe, decentralized recommendation and contextual advertisement systems, to name a few. We validate the proposed approach with simulation experiments performed using real and synthetic datasets.