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Antisocial Behavior in Online Discussion Communities

Justin Cheng, Cristian Danescu-Niculescu-Mizil, Jure Leskovec

2015 · arXiv

Psychology
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1
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6
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5
Months
3
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From the abstract

User contributions in the form of posts, comments, and votes are essential to the success of online communities. However, allowing user participation also invites undesirable behavior such as trolling. In this paper, we characterize antisocial behavior in three large online discussion communities by analyzing users who were banned from these communities. We find that such users tend to concentrate their efforts in a small number of threads, are more likely to post irrelevantly, and are more successful at garnering responses from other users. Studying the evolution of these users from the moment they join a community up to when they get banned, we find that not only do they write worse than other users over time, but they also become increasingly less tolerated by the community. Further, we discover that antisocial behavior is exacerbated when community feedback is overly harsh. Our analysis also reveals distinct groups of users with different levels of antisocial behavior that can change over time. We use these insights to identify antisocial users early on, a task of high practical importance to community maintainers.

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Original HN comments, with labels from simple text rules. A label describes the whole comment and may miss context or irony. Read the discussion to make up your own mind. About the labels

6 selected excerpts · 6 total mentions

diminoten
Recommendation · rule
The work is here: http://arxiv.org/pdf/1504.00680v1.pdf According to the data, FBUs (future banned users, aka trolls) are significantly more readable in their writing than NBUs (never banned users). That's certainly surprising. Also of note is that FBUs tend to reply more than NBUs, which actually meshes with some features of HN -- the inability to reply to a nested comment from within the nest (one has to click on the comment itself to reply -- though this feature has always been somewhat ambiguous and not really deterrent of impulsive replies; I don't even notice it anymore). Also, I think HN deflates the score of posts with many comments, a strategy supported by this…
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line in the paper: "Prior work also identified post frequency as a signal of a low quality discussion (Diakopoulos and Naaman 2011)." An absolutely fascinating paper. What are the consequences, from an IP standpoint, of taking this paper and implementing features based on its conclusions?
Original comment Internet trolls: Proactive policing
room271
Neutral mention · rule
Indeed, I've seen at least one paper where they used Mecanical Turk and aggregated results (by showing the same examples to multiple people) to check for quality. It sounds like they did almost exactly the same thing here. Paper: 'Antisocial Behaviour In Online Discussion Communities' (Cheng et al., 2015) Link: http://arxiv.org/pdf/1504.00680v1.pdf (Search for 'Mechanical Turk' / section Data Preparation -> Measuring text quality.)
Original comment News Feed FYI: Further Reducing Clickbait in Feed
themeekforgotpw
Neutral mention · rule
Definitely not all strategic communications could be detected and blocked. However some research has been tasked on the issue. Take "Antisocial Behavior in Online Discussion Communities" (http://arxiv.org/pdf/1504.00680v1.pdf). This paper, though it terms it 'antisocial', studies online influence operations and is mentioned on NATO's propaganda ("strategic communication") centre for excellence Facebook page (https://www.facebook.com/StratComCOE). The point of having a rule set that can be pushed to like the system described here is that it can be fed information from a centralized task force. Indeed, these systems are used across industries with patterns and rules to…
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detect malware, hacking, and a host of other activity (using formats such as STIX or TAXI). It's unlikely that Facebook itself would be trying to determine whether a post to some content is propaganda - it's more likely that their automated system will apply the rules it receives from information defense agencies. As per your other note, the selective censorship of information is absolutely a form a propaganda of its own. Facebook (and the US government) don't have the best history here and have 100% certifiably censored information to prevent effective organization of (for example) May Day protests. I'm not going to go speak about that at length here - hoping to get some technical clarity from those involved.
Original comment Fighting spam with Haskell
RcouF1uZ4gsC
Neutral mention · rule
I don't think this technique is going to be all that helpful. This is because you cannot consider specificity and sensitivity without taking into account the prevalence. Let us look at the data from the paper [1]. From the chart on page 3, we can see that the percentage of banned ranges from 1.7% to 3.3%. On the last page we have the phrase "Though average classifier precision is relatively high (0.80), one in five users identified as antisocial are nonetheless misclassified". Based on this, I think we have a specificity of 80%, and a sensitivity of 80%. Let us look at 1000 hypothetical users, using 3% as the prevalence. Flagged and Not Flagged represent the output of the…
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algorithm, and Regular and Banned represent "Gold Standard" |Regular | Banned | -------------------------------- Total |970 | 30 ---------------------------------- Flagged |194 | 24 ---------------------------------- Not Flagged | 776 | 6 In this example, the algorithm will flag 218 out of a thousand people as being trolls. 194 of the 218 people flagged are actually not trolls. Doing any sort of automated banning based on this algorithm will I think be unacceptable. I may have some of my stats or assumptions wrong, and I would love to be educated why if that is the case. 1. http://arxiv.org/pdf/1504.00680v1.pdf
Original comment Internet trolls: Proactive policing
sqrt17
Neutral mention · rule
The article is reporting about a scientific study (http://arxiv.org/pdf/1504.00680v1.pdf discussed in https://news.ycombinator.com/item?id=9399090) that specifically talks about "future banned users" without asking why these users would be banned; The rest of the economist article is journalistic speculation. The study authors do report that there's a propensity for polarization, i.e., that "we find a community bias against FBUs: posts written later in an FBU’s life are more likely to be deleted, regardless of whether they are actually worse".
Original comment Internet trolls: Proactive policing
themeekforgotpw
Neutral mention · rule
This is tangentially related to the same general topic, so I hope it is welcomed here. Methods for state censorship are making their way onto content providers online. For example, in the United States we have a system across Twitter, Reddit, Facebook and other sites whereby links will be blocked from publication. A recent academic publication "Antisocial Behavior in Online Discussion Communities" (http://arxiv.org/pdf/1504.00680v1.pdf) has been reported as a boon for 'anti-troll' applications of the internet - though it finds its funding from counter-propaganda funding from the US and NATO. The West more generally will cry out when nations block Western content, ideas,…
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or US funded Civil Society groups - but are fine themselves censoring anti-Western ideas and narratives even when they are not directly part of a mis- or dis-information campaign. Those who have lived both inside and outside the United States are, for the most part, well aware that Americans live inside of an information bubble of American narrative - and that Americans (like every other citizen on Earth) is subject to censorship and to propaganda. The Internet, by a series of laws and technical solutions, is today in the process of being enveloped into this system. I lived through the era where the Internet was free, and miss it. I fear tomorrow's Internet, and the Internet of the day after; I fear that it will continue - and all signs currently point this direction - down a narrowing corridor until it, too, becomes unashamedly part of the same bubble.
Original comment European court decision: Websites are liable for users’ comments

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