Come si ricostruisce il profilo dei lettori dei quotidiani online - Stefania Fragapane; Giovanni Giuffrida; Calogero Zarba (Quaderni di Sociologia, 2010)
In this paper we discuss a data mining application to profile online users on a news website. Such profiles are then used to target users with personalized content in order to increase the overall number of pageviews generated. The additional pageviews provide extra revenue for the online editor. While the proposed system satisfies the online editor to better monetize their content, in our study, we also provide a sociological interpretation of the produced knowledge base. We consider this to be a quite novel approach where scientists from two very different disciplines (i.e., computer science and social science) combine their effort in order to provide a common framework for interpreting and utilizing the information extracted. Both disciplines benefit from a combined approach. From one side the computer scientists can “tune” their data mining algorithms in order to support the different sociological view of the data. From the other side, the social scientists can benefit from the additional information provided by the data mining tool as they provide a new insight for their data interpretation.