Conversations Gone Awry: Detecting Early Signs of Conversational Failure

TL;DR

This paper proposes a method to predict early signs of conversational failure in online discussions by analyzing initial pragmatic cues, enabling timely intervention before antisocial behavior escalates.

Contribution

It introduces a novel framework for capturing pragmatic devices at conversation start and demonstrates their effectiveness in predicting future antisocial behavior.

Findings

Early warning signs can be detected from initial pragmatic cues.

The framework shows promise for real-time intervention in online social systems.

Analysis of pragmatic devices correlates with conversation outcomes.

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.