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Show HN: Testing HN titles against a neural network

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Re: Show HN: Testing HN titles against a neural network

#131

Post by michjedi »

Current 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.

Re: Show HN: Testing HN titles against a neural network

#133

Post by MiroF »

JoeAltmaier wrote: post #122
blauditore wrote: post #68

It'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

So that's a neural network thing? If the input is 'word space' it trains to detect buzzwords? I'm honestly interested - do we hobble our neural networks with our choice of training space? If for instance, the HN-NN-input space including 'prepositions and word-frequency statistics', would the network train for sentence sophistication? Just because those stats were in front of it?

The neural network used here is very weak, it's not going to do much better than word correlations.

Re: Show HN: Testing HN titles against a neural network

#134

Post by jansan »

michjedi wrote: post #131

Current 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:…

So 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.

Re: Show HN: Testing HN titles against a neural network

#135

Post by frankbreetz »

HNLurker2 wrote: post #20

Can a neural net predict Google's stocks if it goes up or down? t. Google employee knowing what do with my stocks

People 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.

Re: Show HN: Testing HN titles against a neural network

#140

Post by fredsanford »

thaumasiotes wrote: post #107
bencollier49 wrote: post #90

Earlier quoted context omitted.

sohpisticated ?

I 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.

>> "I plan to rewrite Linux in Rust - Linus Torvalds" Maybe it's sohpisticated because Linus is going to RIIR?
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