Matthew Bernas
Summary
Antisocial behavior
The article “Antisocial Behavior in Online Discussion Communities” discusses the behaviors and characteristics of a specific category of online users that display antisocial behaviors. These behaviors include making flammatory posts and writing content intended to provoke other users into meaningless, off-topic debate. The writers conduct experiments on a couple online communities to gather and model trends exhibited by these “FBU” users. FBU users are defined as users who show antisocial behaviors and ultimately are banned from the community. The writers studied the posting habits of FBU and NBUs. They found that FBUs typically are more active in a select number of posts compared to NBU. These posts are less readable and more likely to contain swearing and off-topic content. The article discussed a prediction model they were able to create that accurately predicted FBU activity by observing FBU typical behavior. They found interesting trends in their model relating to content quality of both FBU and NBUs. They found that content quality decreases over time for both types of users. They were also able to identify two types of FBUs that differ from the amount of their content that is deleted. This prediction model proves to be effective and is able to predict users becoming FBUs by studying an amazingly little amount of 10 posts.
Reflection
The work discussed in this article is very interesting in that they were able to create such a powerful prediction model that requires only 10 posts to identify FBUs early in their life cycle. This accomplishment came from their accurate definitions of antisocial behavior and their study on how these behaviors change over time. Since they were able to predict if users were going to later develop into FBU, it shows that we can create categories of users describing their roles in online communities. The article showed that we can identify any type of user in a community by observing characteristics that define the type of user and then observe trends over time.
Questions
- What are the possible implications of the results from the experiment to predict future FBUs?
- What can we do with the definitions that we can form from observing certain types of users?
- Can we use a similar process to detect posts that are created by fake accounts?
