LinkedIn, the most popular professional online social network, reached its 300 million users in April 2014. With the increasing interest to its services, LinkedIn became undoubtedly one of these massive repositories of data containing curricular information of professionals from around the globe. In this talk, I'll focus on the different strategies of data collection through the cyberspace in general and LinkedIn in particular. Also, I'll give some details about the scrutiny of both educational and professional backgrounds, mainly by applying data mining techniques, to Uncover/discover potential hidden aspects of the data. Finally, a characterization of these public profiles will be briefly depicted to allow, then, interactions with the audience.
Kais Dai is a Ph.D. Student in Information and Communication Technologies at the University of Vigo (Spain) and member of the I&C Lab. (AtlanTIC Research Center) since 2013. His research interests are focused on Social Data Mining, Learning Analytics and Optimization Techniques. Kais obtained his master’s degree in New Technologies of Dedicated Computing Systems from the National Engineering School of Sfax (Tunisia) in 2012. He worked on several IT projects mainly with the UNIDO (United Nations Industrial Development Organization).