Qualche giorno fa, Radar Blog di O’Reilly pubblica una interessante intervista a Drew Conway sul quale è stato l’impatto dei social media, dell’open source e del datamining sulle scienze sociali.

Per capire chi è Conway e qual è il suo lavoro, metto qui le slide di uno speech sull’uso di R per la social network analysis in ambiente social media da lui tenuto a maggio 2010.

Ovviamente, Conway ha un suo blog molto interessante (Zero Intelligence Agents) che mescola scienza politica, programmazione con il software statistico (open source) R, social media ed altro ancora.

Qui ho messo un estratto delle sue risposte, ma credo che valga la pena di leggere l’intervista nel suo complesso

Open source has also had a tremendous impact on how academics do research. First, open source tools for performing statistical analysis, such as R and Python, have robust communities around them. Academics can develop and share code within their niche research area, and as a result the entire community benefits from their effort. Moreover, the philosophy of open source has started to enter into the framework of research. That is, academics are becoming much more open to the idea of sharing data and code at early stages of a research project. Also, many journals in the social sciences are now requiring that authors provide replication code and data

The second piece of the question is how these technologies affect the dissemination of research. In this case blogs have becoming the de facto source for early access to new research, or scientific debate. In my own discipline, The Monkey Cage is most political scientists’ first source for new research. What is fantastic about the Monkey Cage, and other academic blogs, is that they are not only ready by other academics. Journalists, policy makers, and engaged citizens can also interact with academics in this way — something that was not possible before these academic blogs became mainstream.

[infopusher: Data science is a pipeline between academic disciplines – OReilly Radar].