Social Media and the Challenge of Big Data/Deep Data Approach

As sociologists and media scholars, we have been facing an explosion of data regarding every aspect of our everyday life. We observe the human behavior through this large amount of data that we distribute online as contents and conversations (on Facebook, Twitter, etc.). 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. The digital nature of the information, on the one hand, and their enormous quantity on the other hand, change the phase of recovery and structure of the research data within social media. In other words Big Data have been changing the way we are thinking and conducting the research: 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. To observe this reality means to take into consideration a complex scenario, which is characterized by the contingency of these processes, the affordances of different technological platforms, the networks created by friends/followers, the topical networks generated, for example, by #hashtags, the structure of conversations, and the meaning of generated contents. At the same time, we need to think the relationships between Big Data and Deep Data and consider in which ways the data quality present in the quantitative aggregation (that is, the Deep Data present in the Big Data) is structurally different from the one graspable, for example, through ethnographic approach and in-depth interview techniques.