A new study explains the indexing method that's on the hunt for the web's anti-trolls.
I'm pretty sure I've given above-average effort in the online comforting of others. That's probably a bold, overly-hopeful claim, but (if true) this almost certainly has more to do with with where I choose to participate online--a couple of private messageboards populated mostly by people I consider friends, as well as a couple of condition-specific health messageboards--than me being an above-average dude. Am I good at helping internet people out with their woes? Probably not, but it turns out there's a new indexing method that could sort that out with some accuracy.
Said method is described in a paper posted recently to the arVix pre-print server, courtesy of University of Iowa computer scientist Kang Zhao et al. Their research looks at 500,000 different posts on online health community forums--"80-percent of adult Internet users in the U.S. use Internet for health-related purposes," according to the paper--from 50,000 different threaded discussions over a 10 year period. The goal was to identify where in all of that noise users are successfully making other users feel better. Why does that seem so novel?