[sdoering]

Years ago at pyData Berlin I remember a talk trying to classify comments from three major online newspapers with the question if we. Could detect where a comment was made.

One newspaper was left leaning, the other had the reputation of right wing trolls commenting and one was somewhat in the middle ground with a reputation of the audience being pseudo intellectual neoliberalists.

The 'center' (most typical) comment for these three sites totally was in line with these sentiments. The perfect proof (or confirmation bias).

But the classification didn't work. While there were clear cut cases (one has to love stereotypes) most cases were just neutral. Meaning they could have been made on any of these media sites. Either they were just too short or just not extreme enough.

I feel (used explicitly here) that toxicity is not something that is easily classifiable without deeper understanding of the context. Else, if feeling a comment was toxic was the measure one would need to query all walks of life from extreme left to extreme right and afterwards would probably be left with a lot of toxicity that doesn't tell us much except that different people will find different things toxic.