This is about published text. More like if Google Trends counted word occurrences on webpages. Or if Google Ngrams counted webpages instead of books
People don't write much about non-newsworthy things whereas many people search "burger" anytime they want a burger delivery. The datasets aren't usable in the same way
Edit: not to say it's not a cool product! Just keep this in mind and enjoy using it :)
Someone asked an imo good question (that I was going to vouch for, idk why it was dead), but deleted it. Not sure why, but so I'll not credit the username in case they don't want that and changed some words for stylometrics avoidance
> The concept seems pretty comparable. From the title I had a good idea of what it was; when clicking on it, the visual presentation felt familiar & intuitive. \n\n Being a little less literal can be useful!
That's why I'm pointing it out: the title leads you to think they're the same metric, the page looks visually similar, and so you treat it as the same data type; but when you read the data through this lens, you draw wrong conclusions. It took me a while, scrolling down the examples, before I realised why it felt so off and that my mindset is wrong. It's what's being written about currently, not what people on HN are actually looking for
It's indeed not about being nonliteral, it's for me about having been confused about the data being shown
>Someone asked an imo good question but deleted it. Not sure why
it was me, and i deleted it because i realized my last sentence "being a little less literal can be useful" came across as unnecessarily blunt, which i didn't want. but i wasnt sure how to express what i wanted to say without it being that way. so i deleted it while rethinking my phrasing, and rethinking your comment.
in the end, i kind of came around to understand where you were coming from, so i didnt bother to recomment.
If this project is an ad for their product (Upstash, promising "Highly Available, Infinitely Scalable"), then the last thing they'd want is a hug of death :/
/api/hn -> 502 {"error":"Search entry should have an initialized schema, command was: [\"SEARCH.AGGREGATE\",\"hn\",\"{\\\"$or\\\":[{\\\"title\\\":{\\\"$eq\\\":\\\"anthropic\\\",\\\"$boost\\\":5}},{\\\"text\\\":{\\\"$eq\\\":\\\"anthropic\\\"}}]}\",\"{\\\"by_month\\\":{\\\"$dateHistogram\\\":{\\\"field\\\":\\\"time\\\",\\\"fixedInterval\\\":\\\"30d\\\"}},\\\"top_authors\\\":{\\\"$terms\\\":{\\\"field\\\":\\\"by\\\",\\\"size\\\":6}},\\\"by_type\\\":{\\\"$terms\\\":{\\\"field\\\":\\\"type\\\",\\\"size\\\":4}}}\"]"}
Our startup (~20 people) got slashdotted in 1998 or so. I was the only one randomly awake at the time. Remember watching all the logs from our web server in realtime, ready to immediately kill anything or anyone threatening the overall availability.
512 kbps uplink, I think. Even accidental DoS was trivial. We had a self-hosted little data center at our office with the only available stupidly expensive commercial connection.
Felt some dread having to restart the main (async, single-process) web server a few times to keep things going due to bugs in our code. So many* people on dial-up patiently waiting for the page to load.
Its funny that these days the bottleneck is usually the data layer. Servers are so powerful now that even your average $5 server can handle HN levels of load if configured correctly.
Cool! I want to suggest something, Imagine I want to got to a specific date where some topic was hot, I can read it from your website and then go to that date. But it would be better if I could click on some sort of button, or on the points on the graph to go to that date. It would be easy to implement, you just need links like this:
https://news.ycombinator.com/front?day=2026-05-24
The huge spike of "lk-99" in science & frontier tech is amusing...
This is cool concept, would love a positive/negative sentiment computed for each comment that refers to a given word, so you can see trends of "cloudflare (positive)" vs "cloudflare (negative)" where first one counts comments only if sentiment confidence is greater than say 0.6 and the other one counts comments only if sentiment is less than 0.4 (assuming [0,1] sentiment score)
This is a great project. It'd be fun to look at some of the more popular startups over time, both those that ended up successful and those that didn't.
The topic comparisons are pretty boring and search is disabled. Perhaps I'll remember to return to this. But I can't think of much it gives that plain Google nGram viewer doesn't.
One useful feature would be to normalize by total so that I can see changes in something as opposed to just total site growth. Right now I have to chart a single generic parameter but if I pick poorly it’ll confuse the issue.
It's a HN clone, that syncs with HN that allows you to basically establish smaller private communities who can discuss anything that's on HN without actually being on HN.
It also indexes and let's you search through the DB which I find is really useful to find things that peak my interest.
This looks quite nice! But suspiciously absent data points.. no Java or Go for the languages? Seems odd. No Amazon in companies, yet I think it's often mentioned.
I wondered if "go" got filtered out because it's also just a regular word.
It looks like some of these terms aren't indexed (or the site is just too hug of deathed right now), but I'd like to see the graph of like, social media, iot, cryptocurrency, ai.
great idea! Now, you are running into the same issue Google Trends had to solve: term disambiguation. For instance, "atom" is ambiguous in a comparison of editors like this: https://hackernewstrends.com/?q=sublime&q=atom&q=vscode. Given LLMs it might be possible to use an embedding vector (with context) instead of a text string for indexing, and if you do, this problem might go away.
Almost all of the major vulnerability and hack are just single spikes at the time it happened and it tails off after that… except Stuxnet. Stuxnet is was much more interesting that most other attacks since it was very political and openly published. Of course, the thing that attack was about is still a news headline today as well
one subtle consistency bug that made it hard for me to interpret when I was clicking around: the small thumbnail plot vs the full plot often (always?) seem to use different colors.
The blue / orange gets assigned to the opposite labels in the A vs. B when you click, which made it confusing to understand.
Nice! Would love a brief explanation of the infrastructure. I see the Powered by "Upstash Redish Search", but why choose Upstash Redis Search vs something else?
Great job! I've also been wanting to do similar statistics recently, wanting to know when LLMs becoming the absolute dominant topic on HN. Now it seems like half of the posts were about LLMs.
IMO, using AI to assign keywords to a broader group of strict synonymous keywords would make the comparison much more helpful.
Because in general we want to know the trend of categories more than of a word, asking for “auto pilot” for ex. should include “self driving”, FSD etc.
I would not like this. This is the kind of change that made google search so annoying. (Eg what if I want to track the history of 'self-driving' vs 'auto pilot' in sales pitches? Or more basically, what if the system wrongly interprets me wrongly?) Better to support | or similar old-fashioned search engine syntax and dwis and not dwim.
I also have a seperate page for the "Who is Hiring?" posts, here is the distribution of programming languages over each monthly "Who is hiring?" post in HN ever.
https://hackernewstrends.com/who-is-hiring
A minor suggestion - I'd like to be able to render the current graph taller (full height of my browser window).
Also some sentiment analysis on the "people" graphs would be very insightful (particularly for the likes of Edward Snowdon, Julian Assange, Elon Musk and Sam Altman). Perhaps colour the area under the graph red-orange-green based on the sentiment?
Just my idea. I'm working on a side project https://newsavista.com/invite/ASAD68923E that aggregates news and tracks news trends and changing sentiment on the major stories. With cheap cloud LLMs (and "free" local LLMs) it turns out to be a trivial feature to build.
There are a few technologies with pretty generic names which don’t lend themselves so well to this kind of trend analysis.
I was curious about Atom. According to the trend it’s still neck and neck with VS Code. But are people really talking about Atom the text editor that much still, or other types of atoms?
Has anyone tried to make some sort of algorithm to find cool stuff on HN or sort by upvotes etc? I know it's cool and intended that such things don't exist, but has anyone tried?
So you can create any sort of similar services in a single SQL query and an HTML page.
I also hosted it as a publicly accessible data lake, which you can query from everywhere: https://github.com/ClickHouse/ClickHouse/issues/29693#issuec...
It is also updated in real-time.