Show HN: A tool to analyze Hacker News sentiment on any term in seconds

wongarsu · a year ago

If anything, this tool tracks with my general opinion on sentiment analysis: it would be awesome if it actually worked, but most algorithms just predict everything as neutral.

For example if you search for bitwarden it ranks three comments as negative, all others as neutral. If I as a human look at actual comments about bitwarden [1] there are lots of comments about people using it and recommending it. As a human I would rate the sentiment as very positive, with some "negative" comments in between (that are really about specific situations where it's the wrong tool).

I've had some success using LLMs for sentiment analysis. An LLM can understand context and determine that in the given context "Bitwarden is the answer" is a glowing recommendation, not a neutral statement. But doing sentiment analysis that way eats a lot of resources, so I can't fault this tool for going with the more established approach that is incapable of making that leap.

1: https://hn.algolia.com/?dateRange=pastMonth&page=0&prefix=tr...

team-o · a year ago

I haven't looked in the specific classifications of this particular model, but what your comment shows is the importance (IMO) of having a "no sentiment" class when classifying sentiment. E.g. if someone says "John doe is an average guy", the sentiment to John is neutral. But if someone says "John doe is my uncle" there's no sentiment and it should be classified as that. Perhaps the classifier here already takes this into account, but just thought it was worth mentioning the importance of having this extra class, or a separate pre-filter classifier. In your example I also see many that could be filtered out. E.g. "I store them in Bitwarden not in dotfiles" doesn't contain negative/neutral/positive sentiment, or at least you're not able to tell from just this sentence. I appreciate it's a fine line between neutral and no sentiment though.

stephantul · a year ago

There’s some old work [1] that conceptualized sentiment as an interplay between subjectivity and sentiment. The more subjective a statement, the more “range” sentiment gets. I think this is what you are getting at.

I don’t think it ever gained traction, probably because people aren’t interested in creating an actual theory of sentiment that matches the real world.

[1]: https://github.com/clips/pattern/wiki/pattern-en#sentiment

dataflow · a year ago

> E.g. "I store them in Bitwarden not in dotfiles" doesn't contain negative/neutral/positive sentiment, or at least you're not able to tell from just this sentence.

That's an interesting example because when I read it it sounds to me like something slightly positive, or at least, unlikely to be negative. Because if you had a negative opinion of Bitwarden, you probably wouldn't be storing stuff in it.

Mockapapella · a year ago

I think this is fair criticism for where it's at and mirrors my experience while building the tool. For generative AI at least, the smartest models + a good prompt will waffle stomp our tool in terms of quality.

For example, while testing it on "Founder Mode" there were a couple comments that mentioned something like "I hate founder mode but I really really like this other thing that is the opposite of founder mode..." and then just continues for a couple paragraphs. It classified the comment as positive. While _technically_ true, that wasn't quite the intention.

We think there are some ways around this that can increase the fidelity of these models that won't involve using generative AI. Like you said, doing it that way eats a ton of resources.

wongarsu · a year ago

Just spitballing, but maybe a good tradeoff is to use NLP to find good candidate comments that are likely to contain a sentiment, and then analysing a small number of them with a more expensive model (say a quantized 3B or 7B LLM with a good prompt). The quality over quantity approach

drc500free · a year ago

Almost 10 years ago, I ran a media sentiment analytics product that worked on hand coding. Everything automated that we tested - and that our competitors tried to launch - output garbage. The status quo for media analysis was either averaging a lot of garbage, or paying an insane amount for a very limited scope. We used automated tools to multiply the hand coders, but there was no plausible lights-out solution if accuracy really mattered.

That's completely changed in the last 18 months. All my colleagues in the industry have switched to LLMs. They're seeing accuracy as good as hand coding was getting (these were generally college educated coders), at scale.

Non-LLM sentiment tools were always a bit of a parlor trick that required cherry picking to survive the demo. In almost every case drilling to the actual statements revealed it was wrong on anything involving irony, humor, or even complex grammar. That's changed almost overnight.

I think the finding that hn is "neutral" about MBAs says all that's needed about accuracy here.

zzleeper · a year ago

BTW, which algo did you use to classify sentiment? bert or something related?

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codetrotter · a year ago

I think this is actually one of the very first times I have seen neumorphic design in the wild.

Prior to this I’ve mostly only seen it on dribbble.

I actually like this style a lot, and I wish more apps would use it. But at this point I thought that this style was one that “came and went” before it saw any significant actual use in any apps or OSes. Maybe there is still hope after all :)

Edit: oh and I had to try asking your tool for sentiment about neumorphic design after this of course. It returned my own comment lol :p and it called it “neutral”. Is it only evaluating the first paragraph that the word appears in in the comment? (Also I guess other people more commonly refer to it as “neumorphism” than as “neumorphic design” and maybe that’s why when I asked it for neumorphic design it returned my own comment.)

wongarsu · a year ago

To me, neumorphic design looks like skeumorphism for those cheap interfaces made of one continuous sheet of thin printed (sometimes vacuformed) plastic with the actual buttons hidden underneath. Stuff like [1] or [2]. And while I love skeumorphism, I hate those kinds of plastic interfaces. They always use the cheapest mushy buttons, and the pressable area of the buttons is always much smaller than what the printed buttons suggest. It's probably the one kind of physical interface I hate with a passion, and imitating it digitally doesn't evoke any positive feelings in me.

Still better than making everything flat without shadows and making me guess where I can click, I guess.

1: https://www.alamy.com/stock-photo-finger-pressing-the-button...

2: https://www.alamy.com/close-up-of-clothes-washing-machine-bu...

Edit: just checked, this comment was analyzed as "Sentiment: neutral (Confidence: 79.56%)" on the topic of "neumorphic"

4ggr0 · a year ago

> I hate with a passion, and imitating it digitally doesn't evoke any positive feelings in me.

> this comment was analyzed as "Sentiment: neutral (Confidence: 79.56%)"

I wonder what kinds of heinous things you'd have to write for it to be negative...

Almost comical that this comment is not analyzed as negative.

Mockapapella · a year ago

(the other part of the team that built this here)

Honestly makes me pretty happy you called out the theme. I've always enjoyed this style of design and was sad to see that it never picked up steam. I love how it seems to combine a digital Material design with a more physical and real feeling. I'm doing my part to bring it back.

The tool definitely has some kinks in it that we have plans to iron out over time; we just wanted to get it in front of people to see if anybody would even like it. Right now it's just grabbing the first 256 tokens and categorizing on that, and it grabs the first 5000 comments (split over 5 calls) over the past month.

ranger_danger · a year ago

It's uncommon for several reasons: it's not very accessible, its predecessor skeuomorphism (like Win95 style interfaces) was overdone for decades, and it ignores all the reasons we transitioned to flat design in the first place.

https://www.nngroup.com/articles/skeuomorphism/

https://www.nngroup.com/articles/flat-design/

>Neumorphism never quite made it mainstream because it comes with its own set of problems. The low contrast does not offer sufficient visual weight, making the experience not accessible. Additionally, it is difficult to determine clickability, as neumorphism is often used inconsistently on nonclickable and clickable elements.

Don't get me wrong, I still like the design and I think it's cool, but I understand the reasons why it never got popular.

WantonQuantum · a year ago

An aspect of the UI I really like is the way previous results stay available while doing new ones.

chucksmash · a year ago

Tokens are characters in this context?

I tried "neumorphic design" based on the comment this replies to. It is classified as neutral.

Unearned5161 · a year ago

yeah, looks epic. Makes me think of Superman's spaceship in Man Of Steel , mega clean

Pannoniae · a year ago

(tangential) I wish actual skeuomorphism would also come back....Even in things you can theme, it's just choosing between different flat looks.

tdeck · a year ago

Cool to know that this has a name! For some reason it made me think of some old text character based interfaces like this that had recessed gray form fields:

https://www.cloudwisp.com/exploring-visual-basic-1-0-for-ms-...

philjackson · a year ago

There was a period of time where the Mozilla Suite had this design style. Not sure I liked it much, but the nostalgia is nice.

SuperHeavy256 · a year ago

It looks kinda cheap imo.

bhaney · a year ago

I like the concept and the interface, but after trying one of the suggested examples, I'm not convinced this actually works?

I tried "remote work" like the initial instructions recommended as an example. The graph it gave me showed large spikes of "neutral" sentiment with a few negligible bouts of negative sentiment and even smaller bouts of positive sentiment. The sample comment it gave was from a "Who Wants to be Hired" post where the poster demanded exclusively remote offers, which the tool classified as "neutral" (with 98.7% confidence!)

Very slick tool, but if the sentiment analysis itself doesn't really work well then I don't see what value this could have.

lorddustingale · a year ago

It will definitely work better with larger datasets, we have plans to improve quality.

solardev · a year ago

Hmm, it thinks HN is neutral on crypto. Hmmmm.

Is it actually doing anything?

__MatrixMan__ · a year ago

Apparently we prefer death over Oracle. But on a second search Oracle is then better than death...

No, I don't think it is.

philipwhiuk · a year ago

I guess it's an issue when we dislike two things just as much :P

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ranger_danger · a year ago

My biggest issue when I tried to analyze sentiments was that there is no practical way to bias for sarcasm, such as "it's great if you love pulling your hair out".

stevage · a year ago

A month doesn't seem like a useful time frame? Or maybe I'm misunderstanding the main use case.

Also, you could drastically improve styling on mobile. Lot of wasted space.

Mockapapella · a year ago

Main case right now is to see if people like it (and so that we don't hit Algolia rate limits). You're right, a more useful case might be letting the user customize the time frame.

As for mobile, I am but a humble backend dev, but I agree completely. Will put it on the roadmap. Thank you for your feedback!

Nuzzerino · a year ago

Seems pointless to go through all that effort to chart this over time, and have that time limited to..... a single month.

> you can track trends with it

No, no, you can't.

IgorPartola · a year ago

It would be really interesting to see, in the limit of this tech, how any given comment ranks on the group-think to contrarian scale for every comment you read. There are a lot of signals on HN about comment quality, like karma, account age, reputation of certain individual names, but this could be an interesting one. Wonder what kind of emergent behavior it would drive.