Maximizing the spread of influence through a social network
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
Personalized recommendation driven by information flow
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
User grouping behavior in online forums
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
Targeting online communities to maximise information diffusion
Proceedings of the 21st international conference companion on World Wide Web
Compensatory seeding in networks with varying avaliability of nodes
Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining
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In recent years, companies have started to utilise online social communities as a means of communicating with and targeting their employees and customers, and such online communities include discussion fora. The conversational dynamics of users in fora can influence their neighbours in the underlying social network. We make use of such influence to target specific communities with information, i.e. post in them, because a post is generally shared with the community and not just with individual users. In short, we study information diffusion across communities and show that we can achieve high community (and user) spread using an efficient targeting strategy. In order to achieve this, we use a set of novel measures for cross-community influence and show that it outperforms other targeting strategies on two different data-sets: the largest Irish online discussion system, Boards.ie, and technical support fora, SAP SCN.