I remember (from building a sentiment analysis irc bot[1] back in the day that used the afinn wordlist) that sentiment analysis is effective because robots can do mid-70%-accurate classification, but humans only agree around 80% of the time on 'positive/negative' classification.
So I always wonder, if simple models like the afinn wordlist work at close-to-human levels, how much total value is added by the more robust model. Still very cool!
So I always wonder, if simple models like the afinn wordlist work at close-to-human levels, how much total value is added by the more robust model. Still very cool!
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[1] https://github.com/mrluc/cku-irc-bots/blob/master/feelio.cof... - included the following line of code, which is a coffeescript crime but also a cute sentence: