3 ms·

I'm just starting to dive into NLP and I'm curious if this type of technique could be viable for identifying the same users across multiple social media account

• lomnakkus 9y ago
  I seem to recall a paper a couple of years ago showing that this can already being done quite successfully?!? Don't remember the details, unfortunately. (It kind of seems like it would be "easier" in way since natural language doesn't have to obey any special syntax.)
• xyzzy_plugh 9y ago
  If users have the slightest inclination to attempt to be distinct across accounts, wouldn't that defeat this sort of de-anonymization? If for example I apply different linters or stylers, and don't write docs, and don't use camelCase, and don't write tests, won't I appear to be a different programmer? Can we link IOCCC entries with their author's regular day-job work?
  • hanbura 9y ago
    Stylometry of regular text can be fairly reliability defeated even by people who don't know how it works. It remains interesting because most people don't do that. The code stylometry in the linked paper is interesting because it also looks at things likely preserved by stylers and linters: they parse the code and look at things like the depth of the abstract syntax tree, or the frequency of certain AST-node bigrams. Obviously there's opportunity for a lot more research here. But compared to other variants of stylometry, this approach might be fairly robust