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Building Hater News

kevinmcalear.com

120 pointschippy78 comments

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I appreciate the irony of me posting this "hater" comment, but...

my "most hateful" comment was this:

"Thanks, would love to see your app when it's ready!"

Not sure if it's ready for prime-time.

Maybe you're just not that good at hating ;)

Maybe you should ease up on the sarcasm.

No sarcasm there, just an earnest response to a comment: https://news.ycombinator.com/item?id=7462010

Think you missed the sarcasm in pluies_public's comment :)

I can't evaluate how serious or useful this is but I really like the idea. Anything that might encourage more constructive discussions is a perfectly valid thing to explore. I love the idea of trying to characterize the contributions of different commenters based on their history, including my own. Not just for things like "hatefulness" or "incoherence", which is what this seems to be detecting, but other things as well, like "helpfulness" or "erudition" or apparent areas of interest.

https://github.com/neyer/dewDrop may be up your ally - a formal language designed to make this sort of thing doable..

Woah, I always pondered the idea of doing a formal language for this but it's awesome to see someone else's take on it. Thanks for the link.

I have a dreadful fear that this will evolve into a system for trolls to keep score. "Dude! My h8r score is TWICE yours!"

Funnily enough, this comment how has my second-highest hate-score (the highest is a fairly level-headed comment on drug policy.) Apparently my cunning plan to fake being a nice person on HN is working.

doubleplusgood, mini-citizen. language baduse, rectify!

This link points to a stupid blank page. I disable noscript and I get a stupid horse video. You suck!

scroll down.

Whoosh

That's just textbook Poe's Law at work.

It'd be nice to see the score on a post before you post it - it could keep me from doing something I'll regret.

Most fleshware should have this preinstalled.

Sure if I can read what I wrote objectively. Often not.

I got hater scores of around 2.5% on both my accounts. On each one, the most hated comment was the one where I took the most pains to explain that I liked the user's main point and was just trying to clarify/disagree with a small part, i.e., to be sure I was not dodging the central point.

Reading them, they come off as passive-aggressive. I think that's a useful discovery for me. Thanks.

Don't be a douche. You just got chastised by a lame algorithm.

I like the idea -- sure wish I could try it. It hasn't worked since the original submission for me.

I have a feeling I'm a hater.

Same here I swear a fucking lot in my posts, hopefully the swear word detector ranks me high.

I hope this site stays up, seems lot more fun to game than karma, or rather it would be more challenging to garner karma and HP (hate points).

Sorry, you need to work harder on your hating.

  serf's Hater Score:
    2.36%
  Of The Time Spent Hating.

The worst comment:

  I wish that it showed the previous color scheme if I go back. As it stands I have to go back and then refresh with that URL. (firefox)

The main submission was flagkilled so thought this, more technical post would be more on topic.

It's too bad it was flagkilled, because it is an interesting project.

We unkilled it so discussion can continue: https://news.ycombinator.com/item?id=8517267.

Very gracious of you.

Looks like even this much traffic was enough to take it down, so maybe it's just as well.

Google cached http://webcache.googleusercontent.com/search?q=cache:http://...

Small bug: It seems like the specific comments that you link to also include submissions, which once it encouters that it mismatches all the subsequent 2 character links with the comments they're associated with by an index of 1. I.E.

AA -> links to comment beginning with AA

BB -> links to comment beginning with BB

CC -> links to a link the user submitted

DD -> links to comment beginning with CC

EE -> links to comment beginning with DD

Very cool implementation though.

Thanks! Looking into it! :)

It would be awesome if this was fast enough to run on every user. That way, you could make some sort of leaderboard for Haters.

Clicking the quoted comment on the bottom of the page takes you to the wrong comment on HN.

Yes! I love this idea, can you make it go back further and have a leader board?

Yes and yes. :) The problem with the first one is I have to make an individual API call for each comment currently. If you go past 50 comments it starts to get slowwww. For example, I tried to pull back all of @pg's comments... Bad idea. It's like 13,000 of them. Check it: https://hacker-news.firebaseio.com/v0/user/pg.json?print=pre...

I think I've seen a few archives of HN comments. Maybe grab some of those and only make API calls for newer comments? Also preserve the comments from the API calls?

My most hating comment is:

  'Ah interesting re self - how did you find out about that?'

Which I didn't think was particularly harsh.

I've been too lenient on my architectural taste lately as well. Looking forward to good discussion with the other architects at this site.

"Which profiling tool do you use to target your optimizations?", but then again I am a 2.97% hater ....

Your website sucks. All the content is is smashed in a column with small width so I have to scroll left and right to read each paragraph. This despite there being gigantic 30% of the screen margins on each side. Try to build something even half-worthwhile next time you're at it. I could build a better website easily; you should go back to school.

Intentionally hateful comment by the way ;) Just curious to see how much haternews picks up on it. Although the problem I describe with the content column is real, all the insults and drama isn't at all! For reference: http://imgur.com/St9hAqR

Edit: My intentionally hateful comment shows up as being somewhat hateful, but not my most hateful comment. So not too bad!

Haha. Awesome! :) I'll fix the site and I'll keep improving the model.

Screenshot is FF34 if that helps by the way.

And just a fun side experiment idea: I'm curious how the IBM Watson User-Modeling service would stack up out-of-the-box against how you currently do things:

https://ace.ng.bluemix.net/#/store/cloudOEPaneId=store&servi...

http://www.ibm.com/smarterplanet/us/en/ibmwatson/developercl...

Could make for an interesting blog post if you have the time!

Interesting. I'll check it out, thanks!

My most hateful comment was

- "Yup"

A few things:

1. Thanks for posting my blog post @chippy. :) The actual app ( haternews.co ) kept getting booted off HN...

2. There have been a lot of interesting comments on the three threads on here. People pointed out some bugs and overall issues which I will be fixing (also, the site should not crash half as much now). This is just a fun side project I have been messing around with so I can get better at using data science in various applications. If you would like to help build it out for fun further let me know! Also, feel free to submit a bug or suggestion for an improvement if you really want to.(https://github.com/kevinmcalear/hater_news/issues)

3. I wanted to build the "hater score" for two reasons. First, to see how accurately I could build a model to measure insulting comments in the wild and second (if it's accurate), to see how people would react to seeing how positive or negative they usually are on Hacker news (or other social networks).

4. I wanted to make sure everyone knows that just because something is your "Worst Comment" doesn't mean it is negative. Most people have very low scores and most of your comments are not identified as insulting. (It would be over 50% if it is actually an insulting comment.) So most people on HN are not actually haters. I just had a more "hater" focused design just for fun. There are in fact actual haters though, if you look hard enough.

5. Something I found interesting is clicking the "Back In The Day" checkbox. It takes your 50 oldest comments and analyses them, instead of your 50 most recent.

6. Finally, if you're not sure why some comments are getting ranked higher than others, feel free to look at the training data I used (it's from a kaggle competition from a while back.) and read my blog post. If you don't want to here are additional features I used on top of standard bag-of-words (CountVectorizer):

* badwords_count – A count of bad words used in each comment.

* n_words – A count of words used in each comment.

* allcaps – A count of capital letters in each comment.

* allcaps_ratio – A count of capital letters in each comment / the total words used in each comment.

* bad_ratio – A count of bad words used in each comment / the total words used in each comment.

* exclamation – A count of "!" used in each comment.

* addressing – A count of "@" symbols used in each comment.

* spaces – A count of spaces used in each comment.

If you have suggestions on other features I could collect let me know! I'll also be building a way to get actual training data from HN itself and letting HN users determine if a comment is actually insulting or not so that the predictions constantly improve.

It doesn't seem to work on shadowbanned users, eg. https://news.ycombinator.com/user?id=TempleOS

I'm not sure if this is a limitation of the API or not though.

Hmmm... seems to work for me. https://transfer.sh/TclxF/templeos.png

Here is the API call too. https://hacker-news.firebaseio.com/v0/user/TempleOS.json

Something must have went wrong, sorry!

Right you are, I think I typed it all lowercase or camel case, thanks for the clarification :)

No worries! :)

It's interesting some of the comments that the system decided were negative from my history.

Of all of them, only one was actually negative (and that one was about people that steal AWS resources for cryptocoin mining)

Hopefully I'll have some time one evening to have a bit more of a play with your work :)

Great! I'm excited to hear about your findings. I'll try to incorporate them into the app! :)

Have you ever considered that machine learning isn't fairly dust and that you can't sprinkle algorithms on a criteria that's poorly formulated to begin with and get an objective criteria for evaluation? I mean what is "hate" - insults? expressions of frustration? Sly insults? Sarcasm?

Also, the "most hateful" comment was me quoting someone else's rather unpleasant comment, whereas I'd prefer my distaste for lousy ideas show through more directly.

Great point.

1. I wish everything was made from *fairy dust. How awesome would that be? :)

2. "Hate" is definitely hard to quantify. It's in fact quite difficult to map words to their intentions and get it right consistently (especially within a proper context). So difficult that people set up Kaggle competitions on exactly this. I actually got my "magical" training data from a competition that paid out $10k, which I explained in the article but here it is again:

https://www.kaggle.com/c/detecting-insults-in-social-comment...

They did a great job building a baseline training data set to evaluate several different models on. Which are all briefly explained or at least shown in code in the article. And what "hate" actually means here is the probability that a comment is considered insulting. The "hater score" is just an average of the most recent (or oldest, depending on your settings) comments' probabilities that they are insulting.

3. I read and looked at several different attempts to build something similar by various data scientists who were kind enough to share their findings, including a huge contributor to scikit-learn (https://github.com/amueller).

4. Taking out quoted text would be a great feature to add. I have about 5 or 6 new features I will probably add and see if the model works any better for it, thanks for the suggestion (another person was suggesting the same thing). :)

5. This was just to see how well "sprinkled algorithms" and magical coding works in the wild world of actual comments. I love learning and improving my knowledge base with actual experience so I figured why not build something and see what happens. :)

My favorite part about your algorithm is that it even detects SELF-HATRED! That puts an interesting, and depressing!, spin on the project. My pseudo-unconscious self-loathing was uncovered through my meager number of HN posts. Eerie.

The worst comment detected by your project is an expression of relief in learning that onions will not, in fact, brown in fewer than 30 minutes.

"All your life you're just thinking, "I'M AN IDIOT, WHY WON'T THESE BROWN!?" and then, one September's day, you find out it was all lies... the entire time. Lies all the way down."

I was really, really hoping that you built this in lisp.

(he tried to originally, but(

Please point this at the kernel.org mailing lists. Thank you.

I hate Hater News for giving me a hater score of only 5.48%!

> An error occurred in the application and your page could not be served. Please try again in a few moments.

Your app sucks.

Why does hate have negative connotations? If someone did evil to me, and I can't fight back, what do I have besides hate?

And the app in question doesn't work.

Forget it and move on with your life?

so, is that to say that hate can't add to a discussion? It can certainly detract, but I wouldn't be so quick to say that there are no benefits.

I'll walk knee deep in their spit then. If they can make evil to me and get away with it - why won't they?

Hatred is like a spring - it will eventually go off. That's a mechanism of delayed defence.

On the internet, the native currency is attention. You fight back by refusing to pay them the attention they crave.

This doesn't solve the problem. They go on with doing evil to me.

Because it is negative [1], even if it sometimes might be an appropriate response.

[1] http://i.word.com/idictionary/hate

Fear leads to anger. Anger leads to hate. Hate leads to suffering.

What if I'm suffering already?

Then please spare everyone else in the thread from having to suffer you as well.

Why should I? It's unfair when I suffer and they don't.

Yes. But it's less fair for everyone else to have to deal with your lack of maturity. The world would be a better and more civil place if people would move beyond the frankly medieval concept of justice as retributive parity, and certainly the internet would as well.

It's just words in a box. Unless they're threatening you personally, or doxxing you or something, just take a deep breath, recognize when you're dealing with someone who has neither the capacity or willingness to respect you, and move on with life.

I could not move on very far from Microsoft when they were at the height of their power. Surely I could use Linux but the outside world will try constantly to infect me with something MS-proprietary.

These days they are dying and I'm so glad.

I would humbly suggest that you are far too emotionally invested in something as trivial as the business landscape of software.

I surely am. This is my life. Was my life, anyway.

'Hater' isn't about hate. It comes from 'player-hater', where 'player' is slang for a pimp. Many people disapprove of the lifestyles of pimps, mainly because of their use of women's bodies as an income stream, and the emotional manipulation and physical abuse it takes to keep that up.

Pimps characterized this disapproval as a hatred borne from jealousness of a that lifestyle, masking dissatisfaction with one's own square, lame lifestyle, an expression of one's own inner turmoil, cowardice, and weakness.

Assholes at all levels of society picked up on this sentiment (through cultural colonialism.) 'Hater' now means anyone who criticizes the speaker for anything.

When people said this genuinely, the (invalid) logic was that either:

- people who dislike you care deeply about you (enough to hate you), this proving that everyone cares deeply about you.

- people who dislike you dislike everything, so their dislike doesn't matter.

Both are obviously ridiculous, and now people mainly use the term ironically.

They don't dislike me, they just make me suffer for profit and/or amusement.

When (and if) I'm in position, I'll of course return it to them via manual karma.

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