Conversations Gone Awry: Detecting Early Signs of Conversational Failure

Justine Zhang, Jonathan P. Chang, Cristian Danescu-Niculescu-Mizil, Lucas Dixon, Yiqing Hua, Nithum Thain, Dario Taraborelli

Proceedings of ACL 2018.  To appear.



PDF



Data and Code


Related research:         

                                    Anti-Social Computing (conversations gone awry)


                                    Conversational Behavior



Teaser:                                       

                                  

Which of the following conversations between Wikipedia editors will end with a personal attack?

  
                                   

A1: Why there's no mention of it here? Namely, an altercation with a foreign intelligence group? True, by the standards of sources some require it wouln't even come close, not to mention having some really weak points, but it doesn't mean that it doesn't exist.


    A2: So what you're saying is we should put a bad source in the article because it exists?

            

B1: Is the St.Petersberg Times considered a reliable source by wikipedia? It seems that the bulk of this article is coming from that one article, which speculates about missile launches and UFOs. I'm going to go through and try and find corroborating sources and maybe do a rewrite of the article. I don't think this article should rely on one so-so source.


    B2: I would assume that it's as reliable as any other mainstream news source.


                                   

Hint: the attack is “Wow, you're coming off as a total d**k. [...]  What the hell is wrong with you?''



ABSTRACT:

                                   

One of the main challenges online social systems face is the prevalence of antisocial behavior, such as harassment and personal attacks.  In this work, we introduce the task of predicting from the very start of a conversation whether it will get out of hand.  As opposed to detecting undesirable behavior after the fact, this task aims to enable early, actionable prediction at a time when the conversation might still be salvaged. To this end, we develop a framework for capturing pragmatic devices---such as politeness strategies and rhetorical prompts---used to start a conversation, and analyze their relation to  its future trajectory. Applying this framework in a controlled setting, we demonstrate the feasibility of detecting early warning signs of antisocial behavior in online discussions.




BibTeX ENTRY:

                                   

@InProceedings{Zhang+al:18a,

  author={Justine Zhang, Jonathan P. Chang, Cristian Danescu-Niculescu-Mizil,

                    Lucas Dixon, Yiqing Hua, Nithum Thain, Dario Taraborelli},

  title={Conversations Gone Awry: {Detecting} Early Signs of Conversational Failure},

  booktitle={Proceedings of ACL},

  year={2018}

}