Hacker News Board Hacker News, browsed like a classic message board
Live data from Hacker News

LLM-based sentiment analysis of Hacker News posts between Jan 2020 and June 2023

outerbounds.com

Post reply on HN
Print view View original

41–50 of 79 posts

Re: LLM-based sentiment analysis of Hacker News posts between Jan 2020 and June 2023

#41

Post by aussieguy1234 »

tantalor wrote: post #7

Is this just using LLM to be cool? How does pure LLM with basic "In the scale between 0-10 ..." prompt stack up against traditional, battle-tested sentiment analysis tools? Gemini suggests NLTK and spaCy https://www.nltk.org/ https://spacy.io/

I can see a simliarity here in comparing Java/JavaScript/any other modern, more productive language to C. Yes, both can write more or less the same program, but you'll get the same result with less effort and more quickly with the modern languages. Yes, modern languages will always be slower and heavier on resources than C.

Re: LLM-based sentiment analysis of Hacker News posts between Jan 2020 and June 2023

#45

Post by anonylizard »

aussieguy1234 wrote: post #41
tantalor wrote: post #7

Is this just using LLM to be cool? How does pure LLM with basic "In the scale between 0-10 ..." prompt stack up against traditional, battle-tested sentiment analysis tools? Gemini suggests NLTK and spaCy https://www.nltk.org/ https://spacy.io/

I can see a simliarity here in comparing Java/JavaScript/any other modern, more productive language to C. Yes, both can write more or less the same program, but you'll get the same result with less effort and more quickly with the modern languages. Yes, modern languages will always be slower and heavier on resources than C.

That's inaccurate, because traditional sentiment analysis, or rather the entire NLP ecosystem, is a very niche and underoptimized space.

Its not comparing C against Javascript, its comparing Ada against Javascript. Ada is not going to be any faster than javascript because its too niche and therefore underoptimised.

The theoretical minimum computation required by LLMs is far higher than traditional simple NLP algorithms. But the practical computation cost of LLMs will soon be cheaper, because LLMs get so much investment and use, there's massive full-stack optimizations all the way from the GPU to the end libraries.

Re: LLM-based sentiment analysis of Hacker News posts between Jan 2020 and June 2023

#46

Post by thr0w »

I don't know about this analysis and its conclusions. I'll just use this as a jumping point to selfishly spout my own human observations.

For context, I'm someone who uses HN to search for topics I'm interested in, rather than something like Google or Reddit.

- For anything SF community-related, most hits are from 10+ years ago. Lots of "hey we have a space in soma, any local startups want to hang and drink beers?" or "we have an empty desk in a space in the mission, any hackers want to grab it for free?" - all from around 2012 or prior. Nothing like that seems to happen anymore.

- Starting from around 2016, a heavy anti-technology sentiment appears. Cloud, crypto, AI - all are nonsense propagated by VC types and overzealous engineers.

- Similarly, any thread involving money/labor invariably has an anti-capitalist and/or "unions would solve everything" tangent.

Would be interested to hear if others have observed similar.

Re: LLM-based sentiment analysis of Hacker News posts between Jan 2020 and June 2023

#49

Post by vtuulos »

Mathnerd314 wrote: post #47

> Reply only the tags LLM's are really sensitive to bad or even slightly ambiguous grammar. I wonder if the numbers would differ significantly with "Reply only with the tags, in the following format".

I had the same concern. However, the structure of the output was surprisingly stable. We rejected badly formatted responses: https://github.com/outerbounds/hacker-news-sentiment/blob/ma...

The semantics of the topics/tags could be improved for sure with a more detailed prompt

Re: LLM-based sentiment analysis of Hacker News posts between Jan 2020 and June 2023

#50

Post by daveguy »

anonylizard wrote: post #39
tantalor wrote: post #7

Is this just using LLM to be cool? How does pure LLM with basic "In the scale between 0-10 ..." prompt stack up against traditional, battle-tested sentiment analysis tools? Gemini suggests NLTK and spaCy https://www.nltk.org/ https://spacy.io/

Because LLMs WILL dominate all NLP use cases, whether you like it or not. Its like the linux of operating systems. Sure you can handwrite up some custom OS more specialized for a purpose. But its much easier to just use linux, which everyone understands on a basic level and is extremely robust, and modifying it slightly for the end goal. And saying "Traditional sentiment analysis" tools are "Battle tested" is laughab…

Aside from a half dozen or so zeros, you're right on.
Post reply on HN