Predicting Users' Future Level of Communication Activity in Online Social Networks: A First Step towards More Advertising Effectiveness

نویسنده

  • Florian Probst
چکیده

Many Online Social Networks do not generate sustainable revenues through advertising, even though active usage has reached enormous scales. To enable more effective advertising strategies in Online Social Networks, it is essential to identify users who can affect a large number of friends, acquaintances, or other users in the network. In this context, especially users’ future level of communication activity in the Online Social Network plays an important role. A highly active past, however, does not guarantee high levels of future communication activity. Thus, approaches for the prediction of users’ future level of communication activity are needed. Therefore, we transfer a probability-based method that has been primarily developed to forecast purchasing behavior of customers to the context of users’ communication activity in Online Social Networks. In addition, we demonstrate the method’s applicability and suitability by using a publicly available dataset of Facebook.com.

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تاریخ انتشار 2011