My suggestion was not to train the system on user ratings:
The first is to let a number of sensible people give their troll scores of different Facebook posts and tweets (using the general and vague definition of what is to count as trolling). You would feed this into your algorithms, which would learn which combinations of words are characteristic of trolls (as judged by these people), and which arent’t. The second is to simply list a number of words or phrases which would count as characteristic of trolls, in the sense of the general and vague definition.
So, essentially it would depend on the company opinion.
Anyway, lists of words or short phrases won’t work. Keep in mind that trolls are human intelligences, any AI short of Turing-test level won’t beat human intelligences at their own game.
My suggestion was not to train the system on user ratings:
So, essentially it would depend on the company opinion.
Anyway, lists of words or short phrases won’t work. Keep in mind that trolls are human intelligences, any AI short of Turing-test level won’t beat human intelligences at their own game.