Ethics and interdisciplinarity in computational social science.

During the last few years a growing amount of content produced by Internet users has become publicly available online. These data come from a variety of places, including popular social web services like Facebook and Twitter, consumer services like Amazon or weblogs.
The research opportunities opened up by this socio-technological innovation are, as shown by the growing literature on the topic, huge. At the same time new challenges for social scientists arise. In this paper we will focus on two of the main challenges posed to the growth of the so-called computational social science: interdisciplinarity and ethics. While the searchability and persistence of this information make it ideal for sociological research, a quantitative approach is still challenging because of the size and complexity of the data.
Collecting, storing and analyzing these data often require technical skills beyond the traditional curricula of social scientists. These projects require, in fact, collaboration with computer scientists. Nevertheless developing a common interdisciplinary project is often challenging because of the different backgrounds of the researchers.
At the same time the availability of this content poses a challenge concerning privacy and research ethics. Due to the amount of data and the fact that the real identity of the author is often hidden behind a nickname, it is often impossible to ask the subject involved to consent to the use of their data. On the other hand, especially in the first wave of web 2.0, this information has been – intentionally or not – publicly shared by the users. While a technique of dis-embedding the identity of the user from the content analyzed is often the solution used to bypass this issue, an even more important privacy-related challenge for computational social science is emerging. Due to the wide adoption of social network sites such Facebook or Google+, where a user may decide to share his content with his/her group of friends only, the amount of public data will change and decrease in the future. We will discuss this issue by enumerating a number of possible future scenarios.