论文标题

谨慎的线程:在其在线讨论中主动帮助用户评估和降低张力

Thread With Caution: Proactively Helping Users Assess and Deescalate Tension in Their Online Discussions

论文作者

Chang, Jonathan P., Schluger, Charlotte, Danescu-Niculescu-Mizil, Cristian

论文摘要

对于在线讨论平台而言,不可活力仍然是一个主要的挑战,即即使是善意的用户之间的对话也经常会脱离不文明的行为。传统上,平台依靠主持人来进行 - 或没有算法帮助,采取纠正措施,例如删除评论或禁止用户。在这项工作中,我们提出了一个互补的范式,该范式通过主动提高对对话中现有紧张的认识而直接使用户的能力赋予他们,并在他们参与的对话中积极指导他们,因为他们正在起草答复以避免进一步升级。 作为此范式的概念证明,我们设计了一种算法工具,该工具可直接向用户提供此类主动信息,并在流行的讨论平台中进行用户研究。通过将调查与随机对照实验相结合的混合方法方法,我们就参与者如何利用和对此信息做出反应的定性和定量见解。大多数参与者报告发现这种积极主动的范式有价值,并指出它可以帮助他们确定他们可能错过的紧张局势,并提示他们进一步反思自己的答复并修改他们。当我们的工具警告他们的对话可能会脱轨到不熟悉的行为与在禁用工具的控制条件下,他们的对话有可能脱轨,而参与者警告他们的对话风险有可能脱轨,从而证实了这些效果。这些初步发现突出了以用户为中心的范式的潜力,并指向具体的方向以实现未来的实现。

Incivility remains a major challenge for online discussion platforms, to such an extent that even conversations between well-intentioned users can often derail into uncivil behavior. Traditionally, platforms have relied on moderators to -- with or without algorithmic assistance -- take corrective actions such as removing comments or banning users. In this work we propose a complementary paradigm that directly empowers users by proactively enhancing their awareness about existing tension in the conversation they are engaging in and actively guides them as they are drafting their replies to avoid further escalation. As a proof of concept for this paradigm, we design an algorithmic tool that provides such proactive information directly to users, and conduct a user study in a popular discussion platform. Through a mixed methods approach combining surveys with a randomized controlled experiment, we uncover qualitative and quantitative insights regarding how the participants utilize and react to this information. Most participants report finding this proactive paradigm valuable, noting that it helps them to identify tension that they may have otherwise missed and prompts them to further reflect on their own replies and to revise them. These effects are corroborated by a comparison of how the participants draft their reply when our tool warns them that their conversation is at risk of derailing into uncivil behavior versus in a control condition where the tool is disabled. These preliminary findings highlight the potential of this user-centered paradigm and point to concrete directions for future implementations.

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