Live data from Hacker News

Hater News – Are You an HN Troll?

haternews.herokuapp.com

31–40 of 43 posts

Re: Hater News – Are You an HN Troll?

#34
Hello! I wrote this in on of the other threads about so I figured I would leave it here too.

A few things:

1. Thanks for posting my blog post (https://news.ycombinator.com/item?id=8517727) @chippy. :) The actual app ( haternews.co ) kept getting booted off HN... And now thanks @melling for posting it.

2. There have been a lot of interesting comments on the three (now four) 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.

Re: Hater News – Are You an HN Troll?

#36

So my worst comment included a smiley face... "Ah ok. I looked at it more as something you force on your co-workers :)" Looks like 'ah' implies negativity to the algorithms driving this. Edit: It's also only pulling your 50 most recent comments by default. That covers about the last two weeks for me and is probably why it isn't very accurate. 50 comments is a very small dataset to work from. The other option it gives…

Refreshing, isn't it? It give us a semi-sensible insight on how others may perceive our comments. One of the biggest things I learnt in Australia is never to use irony when you're a foreigner. People either wonder whether you said what you intended to say or it delays their understanding of the joke, if there was any. It's sad, because English coworkers love this kind of humour and they're excellent at not smiling when they do it.

Re: Hater News – Are You an HN Troll?

#37

So my worst comment included a smiley face... "Ah ok. I looked at it more as something you force on your co-workers :)" Looks like 'ah' implies negativity to the algorithms driving this. Edit: It's also only pulling your 50 most recent comments by default. That covers about the last two weeks for me and is probably why it isn't very accurate. 50 comments is a very small dataset to work from. The other option it gives…

Great idea! I'll make another option that does exactly this. I think it's potentially a better way to think about it. Since I have to make an individual call for each comment it gets pretty hairy past 50 but I'm sure I can do it differently in the future. I tried to not put a limit on it at first and realized that @pg has something like 13,000 comments... lol. I could also just pull back every user's comments and run them through the model off line and update it every night. I just need a list of every user :)

Re: Hater News – Are You an HN Troll?

#38

Hello! I wrote this in on of the other threads about so I figured I would leave it here too. A few things: 1. Thanks for posting my blog post ( https://news.ycombinator.com/item?id=8517727 ) @chippy. :) The actual app ( haternews.co ) kept getting booted off HN... And now thanks @melling for posting it. 2. There have been a lot of interesting comments on the three (now four) threads on here. People pointed out some b…

This kind of mindset ("Let's check I have the least negative impact on the community") has to come from the HN crowd. Would it be relevant to adapt it to Reddit?

Re: Hater News – Are You an HN Troll?

#40

So my worst comment included a smiley face... "Ah ok. I looked at it more as something you force on your co-workers :)" Looks like 'ah' implies negativity to the algorithms driving this. Edit: It's also only pulling your 50 most recent comments by default. That covers about the last two weeks for me and is probably why it isn't very accurate. 50 comments is a very small dataset to work from. The other option it gives…

My most negative comment also had a simley face, and can totally see that it's quite negative without it. It's pretty terse and sharp sounding.

*"Fitting all that into 7 minutes will likely lead to injury for someone who is in the audience for any kind of short N minute workout, IMO. I concur with your general sentiment and good intentions though. :)"

I wrote this a couple days ago though, and am a bit miffed because I would have expected to have written a more acerbic comment sometime in the past.

Post reply on HN