On Thu, Jul 25, 2013 at 2:42 PM, Andrew Gray <andrew.gray(a)dunelm.org.uk>wrote;wrote: Also check out https://meta.wikimedia.org/wiki/Research:WikiLove -- Steven Walling https://wikimediafoundation.org/

Yusuke Matsubara and I ran a Mechanical Turk study to classify WikiLove messages a year or two ago. Not what your colleague is asking for, but might give a couple pointers for how someone could perform that study... I think the dataset is still around somewhere too. http://meta.wikimedia.org/wiki/Research:Classifying_wikilove_messages Moral of the story: - about a quarter of WikiLove messages aren't "Hey, great job!". They're help requests, responses to help requests, offers of condolences, welcomes to new users, even some warnings. - the context and content of a message matter, so if you want to track the influence of WikiLove (on # edits? length of participation?) these messages are likely to be "noise" that confounds your analysis. So, if you're interested in the effect of *praise* or *thanks* specifically, you'll want to filter out messages like these. There's also a real-time Wikilove edit filter on enwiki: http://en.wikipedia.org/w/index.php?title=Special:AbuseLog&wpSearchFilt… - J On Thu, Jul 25, 2013 at 2:42 PM, Andrew Gray <andrew.gray(a)dunelm.org.uk>wrote;wrote: -- Jonathan T. Morgan Research Strategist Wikimedia Foundation