Ask HN: How would you design a cringe detector?
I have a dream of making a cringe detector - a program that you could input a tweet or image, and it outputs how cringy it is.
I am thinking, it could use a neural net, or not necessary.
I was trying to imagine, how could that thing work? And actually out of clue.
What do you think? look up “sentiment analysis NLP”. That is what you want, except instead of detecting whether text has a positive or negative opinion, you detect whether it’s “cringe” / “not cringe”. I would start by building a sentiment-analysis model by following a tutorial like [1]. Except instead of a dataset with data labeled “positive opinion” and “negative opinion”, you need data labeled “cringe” and “not cringe”. The hard part is finding and classifying that data: remember that if you just take a bunch of “cringe” and ordinary tweets, you may be training for spurious correlations like “hot take” which your model will misinterpret as being “cringe” [1] https://huggingface.co/blog/sentiment-analysis-python#3-buil... Based on what it would calculate it? It’s a spectrum just like “how funny is this” if trained via reddit, i think you could call any content cringe. maybe by finding people from different segments to rate whether certain content is cringe.