This is not the final version of this paper. You can find the final version on the publisher web page. The Influence of Customer Churn and Acquisition on Value Dynamics of Social Neighbourhoods Przemyslaw Kazienko 1,2 , Piotr Bródka 1 and Dymitr Ruta 2 1 Institute of Computer Science, Wroclaw University of Technology Wyb.Wyspiańskiego 27, 50-370 Wroclaw, Poland 2 BT Innovate, British Telecom Group, Intelligent Systems Research Centre (ISRC), Orion 1/12G, Adastral Park, IP5 3RE Ipswich, UK kazienko@pwr.wroc.pl, dymitr.ruta@bt.com, piotr.brodka@pwr.wroc.pl Abstract. The customers of modern telecommunication service providers implicitly create an interactive social networks of individuals, which both depend on and influence each other through various complex social relationships grown on friendship, shared interests, locality, etc. While delivering services on the individual basis, the social network effects exerted from customer-to-customer interactions remain virtually unexplored and unexploited. The focus of this paper is on customer churn and acquisition, where social neighbourhood effects are widely ignored yet may play a vital role in revenue protection. The key assumption made is that a value loss or gain of a churning or new customer extends beyond the revenue stream and directly affects interaction within local neighbourhoods. The direction and strength of this influence are evaluated experimentally by direct measurements of the total neighbourhood value of the churning customer taken before and after the churn event. Keywords: social networks, churn, acquisition, social value, social neighbourhood, social network analysis, network dynamics, social position, telecommunication social network 1 Introduction A social network is one of the many possible representations of a human community, in which people interact and get into relationships with one another. These relationships can be very complex and usually involve our emotions and feelings. Besides, associations within the social network may result from family dependencies or work cooperation. Moreover, a social network continuously evolves and changes its structure. Every second some new communities arise while the others disappear, some relationships reinforce while the other vanish [15]. In the everyday world, people relay on each other. Thus, their choices and behaviour also influence choices and behaviour of the others [5]. This is the fundamental concept of recommender networks [13, 16] or recommender systems [17] and enacts a significant role in marketing [14], in which people spread information and opinion about products through their mutual, personal contacts.