Social Science in the Age of Big Data

While big data provide us new opportunities to make sense of the world, they do not "speak for themselves" and do not override the need for theoretical models. Contrary to Anderson's argument, theory still matters as it "can help discriminate noise from signal, and provide the right context for the interpretation" (Gonzalez-Bailon, 2013, p. 9). For example, we can use big data to identify key actors and flows of information in digital networks, but based on the findings we may construct different stories. In order to make sense of the findings, we need to use theoretical lenses. 

It was also interesting to read that even though there are different types of actors in networked spaces, the public opinion is still overwhelmingly shaped by a minority of actors. For example, as Gonzalez-Bailon mentioned, Wu et al. (2011) found that about 0.05 percent of Twitter users account for almost half of public opinion. However, I suspect that it may vary in different contexts. Therefore, I think that further research is needed.