What are the Hidden Communities of Reddit? | Hacker News Reader

What are the Hidden Communities of Reddit?

cs.utexas.edu

194 pointseli_awry45 comments

I'm not sure what "hidden" means in the title. See, eg, (http://www.reddit.com/r/proana). There are a bunch of these closed groups.

The author's work seems really useful for detecting spam. There are some people / bots who post a lot of specialist content. They only ever post links to content on domains that pay when visitors click links. These domains have a lot of ads. There's no other interaction on the site.

_NOT SAFE FOR WORK_:

This user (http://www.reddit.com/user/walfa2) only posts content from sites which pay when viewers see the images. The domains have heavy ad content, with popups etc.

Here's an example domain:

(http://www.reddit.com/domain/img1.picfoco.com/)

Once you find one user you can find a bunch of these domains, and the other users posting to those domains, and thus find a few more domains.

With a bit of tinkering you could should a colour coded chart of spam domains; of users that only post content from those domains; and users that never make replies but only make top level comments.

That could be run once a week and (with human oversight) used to remove content which is not good for reddit.

That's a cool idea.

In the original title, 'Hidden' was 'Latent' - communities that de-facto exist even though they are not explicit. 'Latent' would have been a more precise word, but 'hidden' is more accessible.

It's not entirely obvious that posting from a domain that incentizes traffic is a bad thing.

If the posts are upvoted by the community, then it should be seen as a good and not a negative.

One of the oddities of reddit as compared to other social sites is that content owners and traffickers are looked-down upon simply because they can profit from attention.

> It's not entirely obvious that posting from a domain that incentizes traffic is a bad thing.

I agree. To me it's not a problem. But unfortunately some of these posts leak into unsuitable subreddits. In a NSFW porn subredddit it's not much of a problem when someone links to a site heavy with horrible porn ads; but when that link is posted to a non-porn subreddit it's more of a problem.

And, really, Reddit is better as a community rather than a dump for links. So people who have no interaction with the site other than dumping links can be a problem. Being paid when people visit those links can make them more of a problem. They have no interest in Reddit.

> when that link is posted to a non-porn subreddit it's more of a problem.

I think that's a seperate concern. Moderators delete bad posts, and the spam filter operates on a per-subreddit basis.

> Reddit is better as a community rather than a dump for links

I'd agree its certainly different as a community than say Digg, but I'm not sure if its for the better because reddit freezes out content creators from using Reddit to syndicate their content.

People posting links to stuff copied onto a pay-per-click image sharing site are pretty far down the food chain. What worries me is that essentially content-creators can't use Reddit without becoming a part of Reddit's community and 'paying their dues' as it is.

Reddit's mods and users have banned or severely punished even major newspapers who wanted to just post their articles on Reddit, and not become Redditors themselves.

> What worries me is that essentially content-creators can't use Reddit without becoming a part of Reddit's community and 'paying their dues' as it is. > Reddit's mods and users have banned or severely punished even major newspapers who wanted to just post their articles on Reddit, and not become Redditors themselves.

A lot of those content creators toe the line between marketing their content on Reddit, and spamming it.

I have a moderately high karma on Reddit, and sometimes get private messages asking me to help people get submissions upvoted in r/politics, and other subreddits. It almost always sounds shady, and I almost always reply with the same thing - post quality content relevant to the subreddit with good titles.

Newspapers trying to post content to reddit without "paying their dues" is like trying to get free advertising. If you have to pay for ads with money, what's wrong with paying for reddit views with "dues" and becoming part of the community?

Essentially the only way to pay your dues in Reddit is to post content apart from your own, and make bunches of comments to prove that you are 'real person'.

That's problematic because content creators don't want to help the competition, and they have real jobs making stuff so don't want to make reddit their part time job.

Advertisement comes with certain guarantees---pay X amount and you get Y amount of impressions or clicks. Becoming part of a community has no guarantee of success, and even once successful Reddit can always turn against you if they view your posting 1 article per day as "spam" because you work for the newspaper who makes the article.

Some of these issues seem like they could be addressed by in-house people at Reddit better than people on the outside - and I'm pretty sure they're already doing some stuff. One could identify clusters of users who 1) usually only vote for one another's stuff, 2) Vote up things most users vote down, and 3) Link mostly to 'bad' domains and rarely comment. These users could then be screened by hand, and hellbanned. This is the sort of thing that I would start with aberrant voting data though - and that is probably not public for the malicious bots.

> If the posts are upvoted by the community, then it should be seen as a good and not a negative.

The problem with this thinking is that vote fraud runs rampant and is sometimes nearly impossible to detect.

I vaguely remember several years back Reddit added the option for users to allow their subreddit and votes data to be used for research purposes with the hope of building a recommendation engine similar to this. Does anyone know if anything came from that? It would be great if the dataset was publicly available.

Edit: Here are the original threads, I don't think the project got very far. http://www.reddit.com/r/announcements/comments/ddz0s/reddit_...

http://www.reddit.com/r/redditdev/comments/dtg4j/want_to_hel...

The option is opt-in (which is good, the fickle reddit community would revolt otherwise) which means almost nobody uses it. If Reddit would remind their users frequently (e.g. at the end of popular Reddit Blog posts as an aside) or reward people for enabling the option (free Reddit Gold for a week, etc.) I'm sure many more people would sign up.

EDIT: (Sorry for all the parentheticals.)

Why not just anonymize the user data part?

There are startups selling health data this way, I don't think it would be so bad for subreddit subscription data.

I don't think Reddit users would go for that. Also, it's surprisingly difficult to anonymize data effectively without removing nearly all of it.

I'm not so sure about that. I believe the problem has been solved, the solution just isn't widely known yet. I read a paper on arxiv probably a year ago that describes a method that seems pretty straightforward and secure, but I've never seen anything about it since. It involved, essentially, throwing out any records which could actually contribute to a change in a statistical measure. You basically end up finding what aspects of the data are actually identifiable, and throw out any records that contain that. It's guaranteed not to screw up your observations because, by definition, if something is statistically significant it has to show up often enough that it CANT be used to single out a source.

Given the dismal history of anonymization, a paper on arvix is roughly up there with a blogger saying 'I've proven p!=np'...

> It's guaranteed not to screw up your observations because, by definition, if something is statistically significant it has to show up often enough that it CANT be used to single out a source.

What's 'statistically significant' here? The usual p<0.05 convention? You realize that there can be multiple measurements or pieces of data all of which individually have p>0.05 but together have p<<0.05... Information leakage should be measured in bits, not p-values.

(This kind of aggregation is one of the benefits of approaches like meta-analysis.)

I didn't look very far into that, but I think that the issue was that subreddit data wasn't included in the vote dump they did. I actually only heard that secondhand - I could be mistaken.

I just used post and comment histories, which suited my purposes fairly well because the larger project was looking into how memes spread.

Took me a while to find it:

http://www.reddit.com/r/redditdev/comments/dtg4j/want_to_hel...

Here's another version:

https://archive.org/details/2010-reddit-research

OT - both Safari (w/o Flash) and Google Chrome max out all CPU cores as long as this site is open. The visualisation might need an upper limit on the work it is doing per second...

I'm on chrome without flash (ubuntu) and I took a screenshot of chrome using 172% of the cpu!

Here's a copy of the post with just text and screenshots: http://www.cs.utexas.edu/~elie/noscriptnetworks.html .

I developed this on Chrome on a Mac and Chromium on Ubuntu, and it worked on both of those. Sorry it's giving you problems.

It made my Firefox / Windows XP / creaky old laptop freak out, too. Might putting the interactive bit on a separate page to the article be in order, so those of us without the specs to play with the interactive bit can still readily read the article?

Firefox 19 on Window 7, and the page sails by just fine.

I would've hazarded a guess at a Webkit bug, but OP mentioned she developed this on Chrome..

It may "sail fine" but sure left my fans howling too. I don't think this is a browser thing.

Not even a hint of stress on Firefox/OSX

I'd be curious to see the connection between politics/economics and other subreddits.

Such as what subreddits are /r/ liberals, conservatives, libertarians, anarchists, etc likely to follow?

Are liberals commonly in /r/trees? Are libertarians big on /r/economics? Are conservatives avoiding /r/wtf and /r/trees?

Those subs weren't really active enough for me to get significant data in the time I was scraping (Reddit doesn't let you go back very far.) Great idea for a future post though.

This is one only a handful of graphvis-esque visuals that ACTUALLY conveys information effectively, as far as I have seen. Not to mention it is really interesting info! Nice work!

Awesome data. Really interesting to look at, and great presentation.

But there are a few things that kinda bother me with this:

The problem I can find with this data is that it isn't a representation of the reddit hidden communities as a whole, just the hidden communities of those who actually post (only 20% of Reddit).

A question I have is whether these are two-way connections with the groups. It's not clear exactly how the analysis is done 100% (perhaps I missed this portion), but could connections between subreddits be generated by there being a lot of people who post in a very tiny subreddit also posting in a larger subreddit? This means that though someone may like Large Subreddit A, they may not like the more specific Subreddit B. But a lot who like Subreddit B like Subreddit A.

I combatted this in two ways - first, I only looked at the top 433 reddits.

There are always going to be the same people cross-subscribed between A and B as between B and A. This graph is not of the number of people cross-subscribed between two reddits - it's of the sum (number of people cross-subscribed)/(users in A) + (number of people cross-subscribed)/(users in B). So if a lot of people in a tiny subreddit are cross-subscribed, they get a big boost from the first term, but almost no boost if they make up a tiny sliver of subscribers to reddit B.

I did a similar thing with all of the departments of the UW: http://www.sorens.in/posts/2012-8-11-uw-courses

Really cool! Couple of comments:

1. I'm assuming you downloaded comment threads from the front page of each the subreddits you looked at and then looked at the subreddit each of the posters had commented in. How many requests did you end up making?

2. Did you hand select the subreddits you analysed? If so, what criteria were you looking for?

3. Have you thought about doing any more research into this area? I made http://redditgraphs.com/ and was looking into ways of guessing a user's age & gender based on their commenting history. I found some papers about similar sites:

twitter: http://www.aclweb.org/anthology-new/D/D11/D11-1120.pdf

blogspot: http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.136...

youtube: http://static.googleusercontent.com/external_content/untrust... (This one looks the most promising; using their methods, treat subreddits as youtube videos to create more accurate profiles of communities and users. They also examine the propagation of speech patterns which capture the spread of some memes.)

Unfortunately, reddit doesn't have user profiles or name-like user names (so there isn't an easily available training set) and I was having difficulties organizing and analyzing the large amount of data I was downloading, so I put the project aside. There has been basically no research done specific to reddit (http://scholar.google.com/scholar?as_ylo=2008&q=reddit+d...) which is surprising to me because of its size and unique subreddit system.

4. If you want to examine the spread of memes, you need access to old threads. http://stattit.com/ is the best way of getting around the reddit API's 1000 most recent post limitation.

5. Last month, a similar data set (which only looked at reddit) was collected - I think you're trying to do something different and your presention is much better, but you might be interested in the discussion: http://www.reddit.com/r/TheoryOfReddit/comments/126pth/scrap...

I looked at about 60,000 distinct users. But you're right about my overall strategy. I chose all of the subreddits with over some number of subscribers (I forget what the number was now.)I ended up with 433 subs. I filtered out the current default subreddits from this visualization.

One thing I was wondering in terms of reddit research - have you looked into this at all - is that they have users check a specific box if they are ok with their voting data being used for research - even if it's already public. My question then is this - is it somehow wrong to use (already-public) data for research? Anyway, I talk about my original aims for the project in some other comments.

Thanks for the link to stattit. My strategy for getting enough threads for my other project was just to keep a slow scraper running for a month and then go back to it - stattit will be incredibly helpful.

> One thing I was wondering in terms of reddit research - have you looked into this at all - is that they have users check a specific box if they are ok with their voting data being used for research - even if it's already public. My question then is this - is it somehow wrong to use (already-public) data for research? Anyway, I talk about my original aims for the project in some other comments.

Based on the dozens (at least) of papers published each year that use twitter data, I'm pretty sure it's kosher to use public posts. You might want to double check with your irb though. Depending on how you present the information, so users might be concerned about their privacy - I wrote a bot that replied to people posting variations of 'your comment history' with a link to the referenced person's redditgraph and several people said they were creeped out by it (a little more here, if your interested: http://www.roadtolarissa.com/redditgraphs-retrospective/).

Depending on what you are looking for the rate limit might slow you down a lot; you might want to contact the site admins:

> tl;dr If you need old data, we'd much rather work out a way to get you a data dump than to have you scrape.

https://groups.google.com/forum/?fromgroups=#!topic/reddit-d...

Does stattit have an archive that one can download or do they just provide the high-level summary stats shown on the site?

I don't think so; the creator /u/Deimorz is pretty cool, you could try asking him.

Insanely fascinating. Keep working and adding more graphs and stuff. Everyone is going look for their favorite subreddit first, then see how common it is for members of that subreddit to be in to other things they are into.

For instance, I usually read /r/bicycles, but also programming, motorcycles, cars, and 2xc. How many other people have that unique mix of interests?

The bottom interactive graph is kinda neat. Setting zero friction and minimal spring tension and gravity center turns the whole thing into a spheroidal structure much like the accretion of objects in space.

Good work for the visualization of the data. Take a look at http://www.datapointed.net/visualizations/ his visuals are superb.

I go to UT and am on the FAI newsletter and totally get your emails!

Adrian Chen thanks you.

Isn't r/WTF missing from this picture?

Indeed. I took out all of the default subreddits because they added too much noise - everyone starts out subscribed to all of them.

Can you not just flip the switch and get equally useful data - don't look for people who subscribe to a default, but to those who unsubscribe from it?

IIRC that can be hard to tell since you can't get the subreddits that people are subscribed to, just the ones they comment on, or post in. Many people are subscribed to r/wtf but don't post or comment in it.

Hi Eli, neat work!

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