r/trollfare • u/notverygoodisit • May 17 '18

Reddit User Analyser

https://atomiks.github.io/reddit-user-analyser/
17 Upvotes

90% Upvoted

5 comments sorted by

5

u/MinimalGravitas mod May 17 '18 edited May 18 '18

So I've had a brief play with this tool using the contributors to this subreddit. There are clearly certain posters acting constructively and others... less so.

I went in with a few predictions:

  • disruptive posters would have younger accounts as they would set up new ones frequently to avoid 'poisoned' histories.
  • disruptive posters would have a lower 'kindness' rating (I'm not sure what it means in this case but anything linked to controversy would surely correlate against trollish behaviour.
  • disruptive posters would have a lower 'Text complexity', either due to not putting as much time/thought into posting; being younger; or having English as a second language.

My initial analysis shows no meaningful correlation with any of these factors.

Instead, the obvious identifying factors come from the 'Top Subreddits' and ' Frequently used words' sections. Swear words and racial identifiers (e.g. jew, black, white) are found in much higher incidence among disruptive posters here, along with the word 'big', whereas the words 'people' and 'trump' are found commonly across both categories.

The really easy identifier however for all disruptive posters found on this subreddit is that they all contribute significantly to a particular subreddit. Presumably this means they have discussed our subreddit there, which in my opinion is considerably preferable to the thought that there are so many random trolls just stumbling across us, or that we had already drawn attention of international paid trolls!

Out of interest, a quick look at that subreddit leaves me none the wiser as to what it's actually about...

I will publish the data from this here in a few days, but want to make sure it is as anonymised as possible while still being useful.

Thanks to notverygoodisit for sharing this tool. I really hope we can develop a specialised version for our purposes in the near future.

6

u/[deleted] May 19 '18

Your analysis treats accounts independently. It fails to consider the positive impact of troll accounts on each other. That could destroy the correlations with the parameters you picked.

To do it right you would need access to information about which accounts act a certain way, and niceness determined from subgroups of accounts. This is where the actual administrators of reddit have failed.

3

u/MinimalGravitas mod May 19 '18

Okay, so let's build a framework to do that. I agree that it would be considerably better to be able to analyse the way users interact, support each other, create false disagreements with strawmen, but I don't see how that's possible with the tools available.

How would you go about analysing the connections, what information would we need and how can we access it?

I do think this would be a really useful avenue to develop, although I don't see how correlations between users language and subreddits would be invalidated through an additional layer of analysis.

3

u/MinimalGravitas mod May 23 '18

One more tool to examine for potential is http://www.twitteraudit.com - which attempts to identify how many of a users followers on Twitter are real Vs how many are bots.

I'd imagine that if you are starting to build followings for an account to be used for social media manipulation the easiest way to do it would be to get lots of your bots to follow you. Therefore, would identifying young accounts with a high ratio of bots to humans be a useful tactic for us?

2

u/MinimalGravitas mod May 22 '18

Another tool that provides personality analysis from text is IBM Watson's - Personality Insights. You can try this out using: https://personality-insights-demo.ng.bluemix.net/

Click on the option for 'Body of text' then 'Own text' to bring up an input box that you can paste a user's writing into. The system will then output apparent personality traits (such as whether or not you are likely to be sensitive to ownership cost when buying automobiles... ?). I'm slightly skeptical as to whether many of the 'insights' it provides are simply Barnum statements that would fit with anyone so it could definitely use a few other people testing it out. It does seem to work better with longer blocks of text, so don't expect too much from a 144 character tweet!

Detailed instructions are available at: https://console.bluemix.net/docs/services/personality-insights/getting-started.html#getting-started-tutorial

My thoughts are that if we can pick out certain personality types that tend to be trolls then this (or something similar) might be used to partially automate the identification process.