Looking for the author behind NYT op-ed using data science

Awesome! I was actually thinking of doing something similar, but with some key differences:

- try and find transcripts and speeches each "suspect" has given.

- Probably use a classification algo to try and determine who the author could be (most likely using KNN)

- I hadn't determined feature building, but was thinking of a either a simple one-hot encoding, entity embedding, or tf-idf.

I then encountered a moral dilemma -- do I do this and it potentially becomes ammo for messing with someone else's career (when that is not my intention)?

Aren't there ethical considerations in outing the author? Clearly he/she intended to remain anonymous, for obvious reasons.

Interesting. I put more weight on the authors caveats about this method, than on the method itself, which is fine since it was I think just presented as an example of what could be done.

Also, if the person most likely (by this analysis) is actually the one who wrote the op-ed, it was either: - the POTUS, which seems unlikely (although who knows) - the secretary for the POTUS, who types his tweets as well - the one person in the President's circle who he cannot fire

I wonder if there could be a way to prevent this by e.g. paying a bunch of random people to rewrite parts of the text in their “own” style (with a review to ensure the meaning isn’t lost).

I think if the source cares about his/her job, they'd intentionally throw in some misdirection (i.e. lodestar')

This is definitely interesting. However, I have assumed from the beginning that, protests to the contrary notwithstanding, this op-ed was thoroughly edited by someone to prevent such an analytical outing.

https://news.ycombinator.com/item?id=17943416 ...