Privacy Preserving Estimation of Social Influence
Tamir Tassa, Francesco Bonchi · 2014
Exploiting word-of-mouth effect to create viral cascades in social networks is a very appealing possibility from the mar-keting standpoint. However, in order to set up an effective viral marketing campaign, one has first to accurately esti-mate social influence. This is usually done by analyzing user activity data. As we point out in this paper, the data anal-ysis and sharing that is needed to estimate social influence raises important privacy issues that may jeopardize the le-gal, ethical and societal acceptability of such practice, and in turn, the concrete applicability of viral marketing in the real world. In this paper we devise secure multiparty protocols that allow a group of service providers and a social networking platform to jointly compute social influence, in a privacy preserving manner. 1.