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I analyzed 571M Amazon reviews to find the most profanity-filled customer rants

burla-cloud.github.io

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Re: I analyzed 571M Amazon reviews to find the most profanity-filled customer rants

#11

Post by vivzkestrel »

- i saw your other comment that talks about using an open source dataset but i had to ask

- how would you actually go about loading reviews if you really wanted to

- what kind of system would you need to work around the captcha and stuff

Re: I analyzed 571M Amazon reviews to find the most profanity-filled customer rants

#12

Post by jmp1062 »

vivzkestrel wrote: post #11

- i saw your other comment that talks about using an open source dataset but i had to ask - how would you actually go about loading reviews if you really wanted to - what kind of system would you need to work around the captcha and stuff

i would probably use Playwright with custom code, create chunks based on similar products, then run it on a large cluster in parallel (https://github.com/Burla-Cloud/burla).

if you have a single worker trying to scrape a shit ton of products back to back to back you're going to get rate limited or their bot detection will catch you.

Re: I analyzed 571M Amazon reviews to find the most profanity-filled customer rants

#13

Post by jmp1062 »

rawgabbit wrote: post #4

I love this. The reviews' word play tops MacBeth in my book.

i'm just happy they don't censor the comment section haha, makes for funny content.

i also love that people will complain about the vulgar language in a book or movie by writing a review that contains a quote with the vulgar language

Re: I analyzed 571M Amazon reviews to find the most profanity-filled customer rants

#15

Post by reaperducer »

It does taste exactly like formaldehyde and kerosene swirled around with a bit of gas station kimchi that's been warming down the front of a hobo's pants. How do I know? To give this comment validity, I took the liberty of mixing up that exact concoction, then I went to down the train yard and asked a hobo to warm it up for me right on his swampy, fetid hobo taint.

Loved this until I remembered that these reviews are what AI is trained on and influenced by.

But at least he's employing hobos.

Re: I analyzed 571M Amazon reviews to find the most profanity-filled customer rants

#16

Post by skyberrys »

jperryjperry wrote: post #10
skyberrys wrote: post #7

Earlier quoted context omitted.

I love it! Endless entertainment and 0 attempts to get me to stay at the Airbnb.

yeah now that I have the images I want to do some silly shit with it. maybe find the all Airbnbs with satanic decor or like red rooms haha

Find all of the ones with taxidermy in the southwest USA.... It's like all of them. Okay I did find one in Austin without, but it still had cowhide pillows.
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