Thanks to large amount of meta-data available on the SE network, data mining seems to be a popular activity, so much so that it was a sponsored activity on Kaggle awhile back. No surprise then that research (even if not peer-reviewed) is coming out using this data:
Paper and Executive Summary
In this paper, we study the problem of inferring the quality of questions and answers through a case study of a software CQA (Stack Overﬂow). Our key ﬁnding is that the quality of an answer is strongly positively correlated with that of its question. Armed with this observation, we propose a family of algorithms to jointly predict the quality of questions and answers, for both quantifying numerical quality scores and differentiating the high-quality questions/answers from those of low quality. We conduct extensive experimental evaluations to demonstrate the effectiveness and efﬁciency of our methods.
What do you think about the validity of the conclusions and methodology employed in the paper? Is there anything useful that we can use to make the site better, or does it simply state the obvious?
* For the record, I have no involvement with this paper nor the authors. I thought that the meta-community at-large would be interested.