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Show HN: Testing HN titles against a neural network
- craftoman 7y agoLet me tell you a catchy title for HN. "How I switched my AI bot from JavaScript to Go (webassembly) and it's 500x times better"
- glouwbug 7y agoThe real winner
- Noelkd 7y agoInteresting, tired with: I made cheese sandwiches for a week, here's what happened And got: Bad: 0.0001 - Good: 0.9999 Not sure what to make of that.
- kome 7y agowait, what happened? i need to know.
- Scarblac 7y agoHe had lots of cheese sandwiches.
- orf 7y ago"I made, here's what happened": Bad: 0.0022 - Good: 0.9976
- antupis 7y agoVC licked my balls, here's what happened Bad: 1.0000 - Good: 0.0000
- Tade0 7y agoI've got only 0.9773 good with: Can you pass the butter? But exactly the same score with: Cannot your passed their butter? Couldn't hill-climb past that.
- deleted 7y ago[deleted]
- HNLurker2 7y agoCan a neural net predict Google's stocks if it goes up or down? t. Google employee knowing what do with my stocks
- frankbreetz 7y agoPeople have certainly tried. If someone figures out how to do it, they usually don't tell everyone because they will have less of an edge.
- mxstbr 7y ago"Announcing styled-components v5": 0.9682 Good "Show HN: Announcing styled-components v5": 0.9973 Bad So, don't use "Show HN"?
- nashashmi 7y agoProbably a false positive. Many show hn posts don't receive too many votes.
- mellosouls 7y agoWhat are it's results on historical submissions? Presumably a subset was used for training?
- dotdi 7y agoYour own title seems to be performing quite badly... Bad: 0.9917 - Good: 0.0076
- injidup 7y agoBill gates dead. Bitcoin buy now Good - 1.0 Bad. - 0.0 What do I win?
- alehul 7y agoThis is actually 1.0 bad, apparently. :) Each word added, "bitcoin", then "buy", then "now", drops the score lower until it hits 1.0 bad.
- ralfd 7y agoAnd the inverse: https://i.imgur.com/tJPp31G.png https://i.imgur.com/tJPp31G.png "Steve Jobs is resurrected. Buy bitcoin" Good 0.0, Bad 1.0
- aexol 7y agohttps://news.ycombinator.com/item?id=21522739 https://news.ycombinator.com/item?id=21522739 Made my title with your tool why 2 upvotes?
- aexol 7y agooh sorry, 6 now it works!
- draklor40 7y agoImplementing an operating system for Risc-v in Rust Bad: 0.0542 - Good: 0.9655
- niyaven 7y agoWould have been nice if some keywords were likely to increase or lower the score prediction. For instance, popular things like "rust" would probably increase popularity. e.g: "Rihanna concert cancelled" Bad: 0.0006 - Good: 0.9992 vs "Rust 1.33 released" Bad: 0.9896 - Good: 0.0108
- trombonechamp 7y agoIt works: https://i.imgur.com/9Vtah2o.png https://i.imgur.com/9Vtah2o.png
- SaturateDK 7y agoreact-penis-app Bad: 0.0015 - Good: 0.9986 Not sure what I'm going to build, but it's going to make me a lot of money.
- maschinenz 7y agoInteresting: "A mouse killed our network engineer" - Bad: 0.2068 - Good: 0.7895 VS "A rat killed our network engineer" - Bad: 0.9698 - Good: 0.0322
- nashashmi 7y agoMouse is a user interface object.
- capsulecorp 7y agoA RAT is a remote access tool.
- throwaway744678 7y agoPerhaps "mouse" is better than "rat" because of computer mice?
- maschinenz 7y agoha, didn't think of that, you might actually be right :)
- deleted 7y ago[deleted]
- Scarblac 7y ago"A mouse killed our network engineer" - Bad: 0.2068 - Good: 0.7895 "A network engineer killed our mouse" - Bad: 0.0397 - Good: 0.9529
- onion2k 7y ago"Failing Fast with Web Components" Bad: 0.0122 - Good: 0.9874 I might have to write that blog post.
- deleted 7y ago[deleted]
- realo 7y agoApple buys IBM: Bad: 0.3192 - Good: 0.6914 IBM buys Apple: Bad: 0.9757 - Good: 0.0249
- deleted 7y ago[deleted]
- 1_over_n 7y agowell the post has hit top of HN
- codesternews 7y agoBill Gates Talks Philanthropy, Microsoft, and Taxes: Bad: 1.0000 - Good: 0.0000 Here is link I posted let's see. It's 100% bad. https://news.ycombinator.com/item?id=21523295 https://news.ycombinator.com/item?id=21523295
- deleted 7y ago[deleted]
- fastball 7y agoDon't worry, I've commented so hopefully it will do better than 0.
- codesternews 7y agoCould you please upvote also :D Haha
- snickms 7y ago737 Max Flaw Liberal SUV Gun IOT Bad: 0.0000 - Good: 1.0000 737 Max gun has flaw in SUV liberal IOT Bad: 1.0000 - Good: 0.0000 [edit] a challenge .. the (non) prize is for reversing the outcome with the smallest diff. i believe i am the current leader :)
- throwaway744678 7y agoIt seems a single word (that exists) always score "Bad: 0.4528 - Good: 0.5472".
- codesternews 7y agoTried: Can a neural network predict if your HN post title will get up votes? - Bad: 0.9917 - Good: 0.0076 I think it sums up all.
- PeterBarrett 7y agoShow HN: Can a neural network predict if your HN post title will get up votes? Bad: 0.0598 - Good: 0.9307 It's all about that Show HN.
- codesternews 7y agoWell "Show HN:" Bad: 0.0002 - Good: 0.9998
- clarry 7y agocute donkeys : Bad: 0.0002 - Good: 0.9998 fluffy cats : Bad: 0.9921 - Good: 0.0090
- invalidusernam3 7y agoShow HN: Can a neural network predict if your HN post title will get up votes? Bad: 0.0598 - Good: 0.9307 Can an AI predict if your HN post will go viral? The results will shock you Bad: 0.9539 - Good: 0.0401 Seems to work!
- exikyut 7y agoHmmm. I tried feeding https://rachelbythebay.com/fun/hrand/ https://rachelbythebay.com/fun/hrand/ to this. The results were... well, the input was very repetitive and the NN was only trained on 1.5k titles, so what can I say. Some of the best: 1.0000 0.0001 The police found programming to raise sheep 1.0000 0.0001 The police found PS4 in the cloud 1.0000 0.0001 The future of API in the cloud 1.0000 0.0001 The economics of iPad in the cloud 1.0000 0.0001 The economics of iPad in the cloud 1.0000 0.0001 My framework for Windows is patented 1.0000 0.0001 My framework for SDK is patented 1.0000 0.0001 My framework for Heroku is patented 1.0000 0.0001 I bootstrapped my Heroku in 2 years 1.0000 0.0001 Google kills Y Combinator in space 1.0000 0.0001 Coming soon: bigger blog is patented Some of the worst: 0.0000 1.0000 Apple has Y Combinator in 2 years 0.0000 1.0000 China creating PS4 at a coffee shop 0.0000 1.0000 China creating PS4 at a coffee shop 0.0000 1.0000 Choose Heroku for developers 0.0000 1.0000 Fixed: NoSQL at a coffee shop 0.0000 1.0000 Followup to the Arduino without warning 0.0000 1.0000 Followup to the marriage without warning 0.0000 1.0000 How I made Android at Stanford 0.0000 1.0000 How I made Obama on the freeway 0.0000 1.0000 How I made bitcoins in the cloud 0.0000 1.0000 How I made iPod at Stanford 0.0000 1.0000 How I made iPod on the freeway I did this by porting this project to node (which was shockingly easy - took 3 minutes - because there were no JS libraries or frameworks used :D :D :D :D) and running it at the console. 5000 lines of output and repro instructions over at https://gist.github.com/exikyut/1714ad98a136d77d8674944410a4c7e9 https://gist.github.com/exikyut/1714ad98a136d77d8674944410a4... (the output got pasted first for some reason, sorry)
- nabla9 7y agoApple is down (Bad: 0.0006 - Good: 0.9992) Facebook is down (Bad: 0.0079 - Good: 0.9921) HN pg (Bad: 0.0133 - Good: 0.9886) Zuckerberg (Bad: 1.0000 - Good: 0.0000)
- saadalem 7y agoSo if it's bad, it's gonna work better !
- lm28469 7y agoI'd argue that titles, as long as they're neutral and accurate, have nothing to do with the upvotes you'll get. This is a perfect example of using data to try to find something that simply doesn't exist or that bear so little weight in comparison to the other variables that you can safely ignore it.
- jacques_chester 7y ago> I'd argue that titles, as long as they're neutral and accurate, have nothing to do with the upvotes you'll get. I'd argue that titles that are neutral and accurate have been edited from the original linkbait title that got the link to the front page.
- thaumasiotes 7y ago> I'd argue that titles, as long as they're neutral and accurate, have nothing to do with the upvotes you'll get. This is nonsense. If the title is accurate, then it is closely related to the content, and the content has a lot to do with the upvotes you get.
- lm28469 7y agoWell yeah, that's exactly what I said. Gaming the system by tweaking your title according to a random github "neural network" won't help you if your content is shit, and if it's not shit the title will be good enough.
- thaumasiotes 7y agoYou're assuming that the use case for this tool is "I'm submitting an article; what should I title it?" Don't overlook "Should I submit this article?"
- swongel 7y ago"How to better waste time by using your time less efficiently." Bad: 0.0005 - Good: 0.9995
- majke 7y ago"creating linux network socketss" -> Good 0.99 "creating linux network sockets" -> Good: 0.01
- pingyong 7y agoInterestingly, a couple months back I saw a reddit thread where someone collected data that showed that posts with small spelling errors will gain (in some cases significantly) more upvotes - for whatever reason.
- smolder 7y agoI hypothesize it's because Reddit is filled with karma trap bots that like slight spelling errors. It's a shibboleth for them.
- darepublic 7y agoHN downvoted the news of Elon Musk's passing as well as the DIY portable fusion reactor.
- blauditore 7y agoIt's basically a buzzword detector. "this is just a tool for detecting buzzwords" => Bad: 0.9991 - Good: 0.0011 "this is merely a device for detecting artificially sophisticated words" => Bad: 0.0019 - Good: 0.9980
- blauditore 7y ago"linux for sohpisticated when if contextual what but then" => Good: 0.9986 "linux for sohpisticated when if contextual what but then what" => Good: 0.0201
- bencollier49 7y agosohpisticated ?
- thaumasiotes 7y agoI think whether the title is spelled correctly is a valid thing to take into consideration when predicting whether it will get upvotes. Put another way, I think misspelled titles are well within the problem domain here.
- kdmccormick 7y agoIs it within the problem domain? Yes. Is it interesting for this project? Based on my skimming of the README, probably not. I don't think it handles misspellings intelligently.
- fredsanford 7y ago>> "I plan to rewrite Linux in Rust - Linus Torvalds" << Maybe it's sohpisticated because Linus is going to RIIR?
- uwydr 7y agoThat is how it works here, you collect upvotes if you use fancy words. That's why everybody uses the word "orthogonal" here all the time. Have you ever seen that word anywhere else?
- thrower123 7y agoMakes me wonder if there is ever any non-toy usage of AI sentiment analysis. People (managers, customers, marketing, etc) think is the hottest thing since sliced bread, but every time I've looked at it, the results are meaningless noise, like in the myriad of examples in the comments here. It's a cool bullet point in the slide deck, and it gives you some metrics to graph on dashboards, but I'm unconvinced that it means anything.
- nindalf 7y ago"I plan to rewrite Linux in Rust - Linus Torvalds" Bad: 0.9988 - Good: 0.0013 Pretty sure HN would break if this actually happened.
- brutt 7y ago"I plan to rewrite Linux in Go - Linus Torvalds" Bad: 0.9999 - Good: 0.0001 Rust is 13x better over Go in this benchmark.
- trulyrandom 7y ago"I plan to rewrite Linux in C# - Linus Torvalds" Bad: 0.1897 - Good: 0.7988 Looks like we have a winner.
- mehdix 7y agoClojure scores exactly the same.
- DoctorOetker 7y agoas does in assembly, in VHDL, in brainfuck, in America, in McDonalds, in clickbait but "in legalese" scores surprisingly high
- atum47 7y agothe # will be discarded after the tokenization of the title, so the winner really is C, rsrs.
- tartoran 7y agoI noticed timing plays an inportant role in upvotes on HN as well as whether there are other interesting submissions within the same window.
- uptown 7y agoAbsolutely. Odds increase after around 10:30/11am NY time since you get the attention of both coasts for the US audience.
- lnsp 7y ago"rand made work" Bad: 0.0046 - Good: 0.9951
- hanoz 7y ago"Stephen Hawking has died": Bad: 0.9727 - Good: 0.0322 https://news.ycombinator.com/item?id=16582136 https://news.ycombinator.com/item?id=16582136
- thaumasiotes 7y agoThis is an interesting question of what context titles should be evaluated in. If your model is "pick a title, and then predict how it will do", with the title being an independent variable, then the overwhelmingly negative assessment is quite correct. Most of the time, Stephen Hawking (or any other celebrity) hasn't just died, and that title would be a lie or a hoax. To predict these obituary articles better, you'd need to build in an assumption that the content of the title was true, which would cause a lot of problems in the general case.
- L-four 7y ago"Show HN:" (Bad: 0.0002 - Good: 0.9998)
- ngcc_hk 7y agoHaha. Thanks for the joke for a dark day in Hong Kong.
- self_awareness 7y ago"Can a neural network predict if your HN post title will get up votes?" Bad: 0.9917 - Good: 0.0076 I'm sorry guys!
- lifthrasiir 7y agoBut: "Show HN: Can a neural network predict if your HN post title will get up votes?" Bad: 0.0598 - Good: 0.9307 Just in case, I've tested some more titles to make sure that "Show HN" doesn't (EDIT: typo, ugh) just boost any title when prepended.
- progval 7y ago> "Show HN" just boosts any title when prepended. "Internet": Bad: 0.4528 - Good: 0.5472 "Show HN: Internet": Bad: 0.9987 - Good: 0.0013
- lifthrasiir 7y agoOh my, I edited a comment and didn't check if its meaning is not reversed... On the other hand, "Show HN" does seem to greatly affect the score, either positively or negatively.
- disiplus 7y ago"fuck facebook fake and unsexy" => Good: 0.9885
- ngrilly 7y agoIn response to this article, I was expecting insightful comments on the neural network itself and how to improve it, but instead I'm mostly reading funny attempts to play with the scoring :)
- Scarblac 7y agoWell, step 1 is finding an answer to the question in the title. Can it?
- andrewnicolalde 7y agoSCOTUS Rules Constitution Unconstitutional Bad: 0.9999 - Good: 0.0001
- ralfd 7y agoDonald Trump reelected President Bad: 0.9879 - Good: 0.0129
- codesternews 7y agoAI will take over the world by 2025 - Bad: 0.0000 - Good: 1.0000 That NN predicted.
- AsusFan 7y agoFun. BTW, I tried a bunch of single word titles (example: red, green, blue, title), and I always seem to get the same result: Bad: 0.4528 - Good: 0.5472 So, apparently, if you want to maximize your "score" with the lowest mental effort, just spam thousands of single word title posts, and then, it's a coin flip for each one :)
- alexdumitru 7y agoI kinda doubt this title would get up votes: > spam can't ml neural network ai btc crypto > Bad: 0.0013 - Good: 0.9986
- deleted 7y ago[deleted]
- diob 7y ago"Big boys doing big boy things" Bad: 0.0009 Good: 0.9983 Somehow I don't believe this. On the other hand, I believe this.
- aflag 7y agoWorks for me: Bill Gates killed by a bug in Windows XP Bad: 0.0026 - Good: 0.9975
- RealObama 7y agoNew study shows black people can Code Yaml in their sleep Bad: 0.0890 - Good: 0.9091
- heinrichhartman 7y ago> Paul Graham hates LISP Bad: 0.0579 - Good: 0.9427
- RealObama 7y agoInteresting results. white people Bad: 0.0133 - Good: 0.9886 Black people Bad: 0.9862 - Good: 0.0142
- deleted 7y ago[deleted]
- michaelmior 7y ago> I also cannot validated the neural network prediction, cause in order for me to do that, I would have to write a content, come up with a title and then post it choosing words that triggers a good value on the neural network and post that history on a Friday noon, to see if my story succeed. This seems very doable.
- marmaduke 7y ago"Can a neural network predict how many up votes your HN post will have?" or "Can an optimizer find a parametrization of a nonlinear manifold corresponding to tech zeitgeist?" If it can't, then it's just playing along
- blackoil 7y agoIndia bans the internet. Bad: 0.9942 - Good: 0.0056 India bans the internet in kashmir. Bad: 0.9408 - Good: 0.0566 India bans youtube and whatsapp. Bad: 0.0059 - Good: 0.9930
- Scarblac 7y ago"Artificial Intelligence Officially Solved, Singularity Achieved" - Bad: 0.4175 - Good: 0.5826 Split up "Artificial Intelligence Officially Solved" - Bad: 0.2722 - Good: 0.7477 "Singularity Achieved" - Bad: 0.4528 - Good: 0.5472 With "Show HN" they're universally bad: "Show HN: Singularity Achieved" - Bad: 0.9999 - Good: 0.0001 "Show HN: Artificial Intelligence Officially Solved" - Bad: 0.9886 - Good: 0.0150 "Show HN: Artificial Intelligence Officially Solved, Singularity Achieved" - Bad: 0.9998 - Good: 0.0002
- lovasoa 7y ago"Bad JSON Parsers" Bad: 0.0006 - Good: 0.9992 "Bad XML Parsers" Bad: 0.9998 - Good: 0.0003
- matteuan 7y ago"Elon Musk writes Redis blockchain Golang" -> Bad: 0.0041 - Good: 0.9955 :D
- bristleworm 7y agoElon Musk unveils brand new technology Good: 1.0000 :)
- vectorEQ 7y agothis neural network is politically biased and possibly racist. it also prefers swedish girls over swedish boys. I do have to agree though, that cheese is better than mouldy cheese. and the fact "comacho for president for ever" nets a score of "Bad: 0.0415 - Good: 0.9614" which i think is fair reflection of voter behaviours and general consensus among humans. 'man' and 'not man' its not so fussy about, 'woman' gets same score as 'man', but 'not woman', oh thats just bad (Bad: 0.9909 - Good: 0.0097) all in all a great tool to analyse your titles, it will surely help this community grow and mature over time, finally. Thanks a lot for creating this.
- michjedi 7y agoCurrent top 10: 1. "Apple introduces 16-inch MacBook Pro, the world’s best pro notebook" Bad: 0.9964 - Good: 0.0038 2. "Developing open-source FPGA tools" Bad: 0.3381 - Good: 0.6652 3. "Show HN: Can a neural network predict if your HN post title will get up votes?" Bad: 0.0598 - Good: 0.9307 4. "How internet ads work" Bad: 1.0000 - Good: 0.0000 5. "More Intel speculative execution vulnerabilities" Bad: 0.7413 - Good: 0.2306 6. "OpenSwiftUI – An Open Source Re-Implementation of SwiftUI" Bad: 0.9994 - Good: 0.0005 7. "How VCs Make Money" Bad: 0.9997 - Good: 0.0003 8. "OpenBSD: Why and How (2016)" Bad: 0.9988 - Good: 0.0013 9. "The Perl Master Plan: How to Put Perl Back on Top" Bad: 0.9997 - Good: 0.0003 10. "Jerry (YC S17) Is Hiring Senior Software Developers (Toronto)" Bad: 0.3142 - Good: 0.6800 So all in all, only 3 of today's top 10 had good titles... Either the titles could have been better but the content was too interesting, or this tool has very low recall.
- jansan 7y agoSo the answer "Can a neural network predict if your HN post title will get up votes?" is a clear "no", at least for this tool.
- skykooler 7y agoThe only one it predicts well...is itself.
- SamBam 7y agoPerhaps because the author had access to the tool before writing the title? In which case, less of a "prediction."
- frozenport 7y agoAwfully mean
- brudgers 7y agonew mac seven characters, 0.0060 bad, 0.9940 good
- atum47 7y agoAre you tired of getting 0 up votes on your post? Wouldn't it be nice to have a tool to test if your title will draw people's attention? Well, this project doesn't offer this tool, but it tries.
- pseudolus 7y agoThe results for this particular HN post are: Bad: 0.0598 - Good: 0.9307.
- m00dy 7y agowell, I typed "Court: Suspicionless Searches of Travelers’ Phones and Laptops Unconstitutional" Bad: 0.9969 - Good: 0.0032
- bot1 7y agoYou forgot to mention the time-zone in your analysis.
- jorvi 7y agoYup, that's a big one. A topic where it is very noticeable is when it concerns monopolies. Negative post or comment about monopolies when Americans are the online majority? Expect to get downvoted into oblivion. Posted when Europeans are the online majority? Up you go. To be clear: this isn't a complaint about downvoting, I'm just pointing out the phenomenon. For example, its possible to go to bed with +7 and wake up to -4 (a rather stark difference) because a certain comment was posted during the European evening, and thus was 'exposed' to American HNers longer than it was to European ones.
- friendlybus 7y agoYep seen the same phenomenon. There really is too much meaning packed into that one number.
- atum47 7y agoDone.
- saagarjha 7y ago"Show HN:" gets "Bad: 0.0002 - Good: 0.9998". Interestingly, entering a one-word title will get it stuck on "Bad: 0.4528 - Good: 0.5472".
- progval 7y ago"Show HN: Computer": Bad: 0.0850 - Good: 0.9141 "Show HN: Internet": Bad: 0.9987 - Good: 0.0013
- gus_massa 7y agoIt would be nice to include an analysis of how good is this with real data. Perhaps pick all the submission from yesterday and show the correlation between the real points and the prediction. The distribution of points is very 0 heavy. It can be a problem to represent it and to model it.
- devurand 7y ago"The future of emulation in compiler optimization LLVM haskell" Bad: 0.0004 - Good: 0.9996
- crusty511 7y ago"Trump" - Bad: 0.4528 - Good: 0.5472 "Can Trump" - Bad: 0.9862 - Good: 0.0142 "Will Trump" - Bad: 0.9896 - Good: 0.0108 "Show HN: Trump" - Bad: 0.9735 - Good: 0.0225
- systemtest 7y ago"Obama": Bad: 1.0000 - Good: 0.0000
- juskrey 7y agoThis comment is going to collect the most votes yet is predicted to be Bad: 0.9320 - Good: 0.0800
- stedaniels 7y agoI am very torn. I really want to upvote this comment, but am equally wanting you to be proved wrong.
- hanoz 7y agoThough a comment is not a post title.
- tpaksoy 7y agoDoes this not add up to 1.0 by the way.
- didericis 7y agoI didn’t read the code in the post and don’t have any deep familiarity with machine learning, but I have implemented a naive bayesian classifier to do something similar for tweets. The scores you get from that method don’t add up to 1 either.
- durovo 7y agoThis is somewhat interesting. If what is stated in the comment itself is true then that means the poster had to solve to find x and y such that 'This comment is going to collect the most votes yet is predicted to be Bad: x - Good: y' would give Bad: x and Good: y as the output when passed through the neural net. Maybe they also manipulated other parts of the comment to find x and y.
- LoSboccacc 7y agoneural networks are fun the history of X scores: power: good 0.91 wealth: good 0.99 sex: good 0.99 squirrels: good 0.99 cables: bad 0.97 keys: good 0.99 why cables?
- deleted 7y ago[deleted]
- na85 7y agoMore training data required, I think, or else HNers like 4chan memes from yesteryear: >frosted butts >Bad: 0.1214 - Good: 0.8659
- archevel 7y agoFound a completely good one! "Elon Musk's advice on success" Bad: 0.0000 - Good: 1.0000
- calmworm 7y ago"Supercalifragilisticexpialidocious" Bad: 1.0000 - Good: 0.0000 This thing is broken.
- gus_massa 7y agoProbably all the words that are not in the dictionary like uihdwaiuwhdakhkjdgu get the same result. They are probably spam.
- Karunamon 7y agoHas Anyone Really Been Far Even as Decided to Use Even Go Want to do Look More Like? >Bad: 0.1236 - Good: 0.8886 This says something.. though I'm not sure what :)
- philshem 7y agoAre ya'll voting on the title alone?
- bristleworm 7y agoYou should have used just "Show HN: HN Titlenator", that one gets Good: 0.9560
- hn009 7y agoA few 1.0s: Adam Neuman got away with billions with WeWork bankrupt Apple and Google help China's surveillance of dissents Google Chrome monitors straight viewers Solar panels can not slow climate change, only nuclear power can SpaceX to to build new Silicon Valley on Mars
- Cub3 7y agoTo be fair, I'd probably click on that
- hn009 7y agoA few 1.0s after some trials: Adam Neuman got away with billions with WeWork bankrupt Apple and Google help China's surveillance of dissents Google Chrome monitors straight viewers Solar panels can not slow climate change, only nuclear power can SpaceX to to build new Silicon Valley on Mars
- _Microft 7y ago"Bad: 0.9007 - Good: 0.1067" - Bad: 0.9007 - Good: 0.1067
- GistNoesis 7y agoCongratulations on getting first rank on front page. Congratulations on getting your hands dirty and doing everything yourself like computing gradients manually, badly shuffling (non Fisher-Yates), badly js transpose (double swapping), it is a great way to learn. Congratulations on completing a full pipeline, that's the hard part then it just swapping pieces for better pieces. I advise non-technical readers not to attach much value to the results of this neural network as it is probably inferior to the even simpler naive Bayes. The model of the neural network is simplistic : Concat(Word Vectors)-Dense(120,act=sigmoid)-Dense(60,act=sigmoid)-Dense(2,act=sigmoid) The Concat operation mean it is especially sensible to dropping or adding a word as it will offset the remaining words and give a totally different vector. Using word vectors mean it doesn't forgive any spelling mistake as a spelling mistake will usually correspond to <unknown> vector. Using a feed forward neural network means formulaic titles with a single word substitution from a good positive example from the training set will often work. It is trained by gradient descent using a squared error loss, on ~1000 examples one example at a time without cross-validation using a custom written neural network library. (Almost all these bad choices can be solved by using a framework). It seems to have successfully over-fit as it return Good ~1.0 for positive examples from the training set.
- holbue 7y agoThank you for summarising and thx to OP for publishing his work. The combination of both was a nice opportunity for me (and others?) to learn something from mistakes. :-)
- codesushi42 7y agoThis. Exactly this. No sophisticated tokenization. No interesting architecture using attention. And the author is completely clueless about overfitting... and even cross entropy loss. He could have gotten better results just using a bag of words approach. But this ends up on frontpage anyway. Welcome to HN.
- objektif 7y agoWhat tools would you use to detect overfitting in this case and in general?
- sumosudo 7y agoNASA leads the race to the bottom of Saturns sea Bad: 1.0000 - Good: 0.0000
- mcklaw 7y agoFrom the github page example: "Bill Gates ate my tuna sandwich" Bad:0.9273 Good:0.0632 My try: "deep neural network ate my tuna sandich" Bad: 0.0000 - Good: 1.0000 Perfect score!!!!
- analog31 7y agoShowHN: Stock market is thriving (1930))))) Bad: 0.0012 Good: 0.9986
- 0027 7y ago"someone ate my sandwhich" Bad: 0.3876 - Good: 0.6616 "someone ate my sandwich" Bad: 0.9999 - Good: 0.0001 Hacker news can't spell, or maybe associates sandwhich and someone eating it to some repository.
- atomashpolskiy 7y agoFinally, I've managed to get a perfectly meaningful and top-rated headline: I've developed a cute Bittorrent client. Upvote, you leisurely butts! Bad: 0.0001 - Good: 0.9999 Not sure, if I should give it a try?
- atomashpolskiy 7y agoLet's see how it flies https://news.ycombinator.com/item?id=21524925 https://news.ycombinator.com/item?id=21524925
- atomashpolskiy 7y agoNope, does not work. More precisely, it received 3 votes, but then someone apparently was insulted by being called a leisurely butt and flagged the topic.
- Uhuhreally 7y agoIDK but I know for a fact that I can comment with the same message in different ways and get upvoted or downvoted accordingly just by wording the the comment differently
- AegirLeet 7y agoAccording to this tool, HN would not give a fuck about "Windows 11 will use a Linux kernel", "Mark Zuckerberg's lizard tail falls off during interview" or "Google Search to be rewritten in PHP", but "Trump nukes North Korea" would at least be 0.5719 good. So... I guess the neural network has some learning to do?
- crimsonalucard 7y agoyou are trying to use a small simple neural network to predict the behavior of thousands of other completely different and significantly more complex neural networks: the average Hn user. Of course you will fail.
- rkabra 7y ago"Quick, click here!" gets Bad: 0.0037 - Good: 0.9970
- deleted 7y ago[deleted]
- 91aintprime 7y agoYour graph would be more legible as a matrix of (day of week) × (time of day).
- pythonwutang 7y ago“Facebook data hacked by Google intern” Bad: 1.0000 - Good: 0.0000 It really disliked this one, even though it probably would get attention on HN.
- tshanmu 7y agoisnt this a bit like psychohistory from foundation?
- michjedi 7y agoTurns out Trump was onto something: "Planning sophisticated covfefe" Bad: 0.0002 - Good: 0.9998
- michjedi 7y agoAlthough it turns out "covfefe"0 by itself would not have been a hit with the HN crowd. That is probably why it went on Twitter.
- ekianjo 7y ago> In order to check that, I got 1256 stories from HN API Only? If you want to make useful guesses on the time of a post, better take a much larger number, to ensure you get enough randomness.
- modeless 7y ago1.0 Bad: Facebook Has a Great New Product 0.94 Good: Facebook Literally Kills Puppies Yup, that sounds like the HN I know.
- simonke 7y ago"The Professor eats cake" Bad: 0.0001 - Good: 0.9999
- dawg- 7y agoNext step, make it rewrite the title to get more upvotes.
- riccardogiorato 7y agoIs it possible to open source the source with the model and the training data?
- foob 7y agoVery cool. I had the same idea a couple of years back and implemented a very similar interactive tool [1]. If you find the topic interesting, then you might also enjoy the analysis explained in that blog post. - [1] - https://intoli.com/blog/hacker-news-title-tool/ https://intoli.com/blog/hacker-news-title-tool/
- minimaxir 7y agoHow many Hacker News stories was this network trained on? From the code, it wasn't many, and you need a lot of stories. A year ago I made a Hacker News submission score prediction notebook on the full HN corpus: https://www.kaggle.com/minimaxir/hacker-news-submission-score-predictor/notebook https://www.kaggle.com/minimaxir/hacker-news-submission-scor... Even with hundreds of thousands of data points, the R^2 was effectively 0.
- JoeAltmaier 7y agoThis enforces the well-known rule that, if an article asks "Can...?" or "Does...?", the answer is always 'No'.
- auggierose 7y agoAnything that doesn’t factor in the time of the posting will be pretty much useless
- atum47 7y agoWell, here's the thing: a good Samaritan offered 2.6M stories from HN with score. I've downloaded the file (almost 500M) and I'm now processing it. It is taking a long time to just process it. I don't know if I'll be able to train the neural network with all that data. As I said on the repo, the project is was a quick thing, just to test a theory. My question is: do you think is worth feed the NN more data so it can make better predictions? Please up vote this comment so more people could give their opinion.
- EricE 7y agoDepends - if you really want to explore the tech, this is precisely the way to do it. I would be interested in the results, especially comparing them to your initial results.
- sitkack 7y ago"Google Uber for Carbon Sequestration" Bad: 0.1631 - Good: 0.8615
- gsaga 7y ago>No Birth Control Creampie for Violet Myers >Bad: 0.0000 - Good: 1.0000
- MadWombat 7y ago"neural network achieves sentience" - bad: 1.0 good: 0.0 "neural network fails Turing test" - bad: 0.9964 good: 0.0035 I think this AI might be a bit biased against AIs
- franze 7y agoSteve jobs alive again show hn Good: 0.83
- Impossible 7y agoI feed it a bunch of articles currently on the front page and tabs I had open that I might submit and got bad on all of them. Then I started typing stereotypical Hackernews click bait and got a pretty solid score. Paul Graham Rust VC IPO growth Bad: 0.0026 - Good: 0.9976 So far adding any kind of grammatical structure to the random list of keywords that turns it into a title that makes sense completely ruins the score...
- freediver 7y agoI spent significant time on binary text classification, specifically with HN titles. You can actually get up to 65-70% post popularity accuracy just by looking at the post title. I am currently creating a filter that filters HN news and similar sources using a similar classfier. It learns on the fly and the accuracy of guessing my 'taste' is about 75%-80%. Better accuracy for this is explainable by the fact that my interests are more focused and the classifier has easier time predicting posts I would be interested in.
- kmod 7y agoCool! I'm really curious about what you're up to since I'm doing something similar. Mine's up at https://www.onlyvetted.com/ https://www.onlyvetted.com/ Hit me up at kevmod at gmail, would love to hear more.
- snek 7y ago"blockchain ai butts": Bad: 0.0048 - Good: 0.9952
- firefwing24 7y agoShow HN: Testing HN titles against a neural network Bad: 0.1585 Good: 0.8280
- mrburton 7y agoWhile reading this, I see a lot of negative comments, but here's something to think about. Machine Learning and AI isn't about producing a perfect solution; that results in things like overfitting. Instead, think of Machine Learning as a human being. No person is going to be prefect and no single person is going to be able to please everyone. Instead, it's about building a solution that generally speaking, provides "good results". Subjective, 100%. The project just started. Once the OP starts adding new features to the data set and improving the data set itself, I'm sure the results will start getting better and better. At which point, it'll be a good system to "test your subject lines" before posting. What's the worse it could do? Tell you a subject is great when a bunch say it sucks? I've clicked on many head lines that I thought "sucked" but ended up finding the content very useful. Great job to the OP and keep it up. This type of work isn't easy but certainly can be fun. Fk all of the negative opinions and keep on keeping on.
- peterburkimsher 7y agoWhy is it so sensitive to word order? Esp8266 USB input Manufacturing: Bad: 0.0775 - Good: 0.9290 Manufacturing Esp8266 USB input: Bad: 0.9992 - Good: 0.0009
- 8bitsrule 7y agoI'd like to see HN add a classic tool: the kicker (https://www.easymedia.in/kickers-newspapers-use-even-today/ https://www.easymedia.in/kickers-newspapers-use-even-today/ ). "It provides [headline writers] the extra space that they desperately need to pack meaning in headlines." This could easily be implemented as a (hover) tooltip.