OK, so I've learned from this paper that this sort of paid postings to influence public opinion occur systematically by trained teams in China. But my praises

OK, so I've learned from this paper that this sort of paid postings to influence public opinion occur systematically by trained teams in China. But my praises end there. I don't trust much their machine learning detection approach. But before we get into that, let's describe what they did. These researchers collected about 21,000 comments from a news site representing 552 users. The researchers then manually selected which of these 552 users they thought to be paid posters without any external confirmation. According to their methodology they assumed stupid comments or contradictory comments were by paid posters. The approach from here was to do lots of fancy math on novel comments not screened by the researchers, and make a classification on if these novel comments were by paid posters or not. If you haven't guessed it by now, the flaw here is the researchers assigning which commenters they thought were paid or not, based on the stupidity of the comment. Its pretty easy to manually classify e-mail spam, but I'd have a hard time classifying a paid public opinion shill based on a comment. Furthermore, if the researchers are using the intelligence of the comment as a marker, my experience with youtube comments, r/politics, and a few other internet forums leads me to believe that there's no shortage of stupid, contradictory ideas espoused by real unpaid people.