Content created by users online (UGC) is a new kind of research topic in the field of social sciences and it gives us particularly promising data. Defined as qualitative data, it is undeniable that being spontaneously created by the users for an unknown audience places them in a particular condition. In addition to it we have to consider the consequences, for the empirical research, of the ease with which those data are researched and found. This paper focuses on how Big Data are changing the way we are thinking and conducting the research. They lead us to the Computational Social science, which enables a transdisciplinary approach: a sociological observation of online social phenomena using methods of data managing and data collection borrowed from the computer science. As a consequence, we are able to analyze in depth a wide range of data as never before, facing a scenario rich both of opportunities and critical points to not understate. It is necessary, at this point, to keep clear in mind structures and affordances of the platforms, characteristics of the analyzed network, the relation between online conversations and social ties and in the end, all of the previous points have to be framed in a longitudinal perspective in order not to push down the data in an eternal present avoiding to consider their evolution over time.
Keywords: Computational social science, social network, User Generated Content, Big Data, Methodology