Ask HN: How would you design a cringe detector?

2 points·mib32··3 comments

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?

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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.

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