CHS: Small: Automatically Identifying Misunderstandings of Social Intentions in Online Conversations

该项目将开发理解社交媒体中的误解的新方法，并将设计新的干预措施来防止或减少误解。随着时间的推移，在线对话往往变得越来越充满敌意，导致诸如网络挑衅、人身攻击、骚扰和欺凌等破坏性行为。先前的研究表明，在某些情况下，这些出轨可以追溯到恶意的个人和社会传染。然而，在其他情况下，干扰可能是由简单的误解造成的：读者可能误解了海报的社会意图，认为一条信息是友好的、敌意的或攻击性的，而实际上恰恰相反。该项目将创建一个框架，用于理解社会意图何时以及为何被误解，自动捕捉这种误解对在线对话的轨迹和结果的影响的计算方法，以及可能有助于防止误解的工具。在社会计算和人机交互的背景下，该研究结合了自然语言处理和计算机介导的通信专业知识。与其他研究信息内容是如何被误解的工作不同，本研究旨在了解识别信息的语用力量的问题，例如，它是作为命令还是请求，笑话还是敌意的评论。这种“语用失误”的根源在于信息的字面意义和预期意义之间的区别，以及不同社会文化背景的读者对其中一种或另一种的不同倾向。这种现象在网络上尤其严重，人们在线下用来消除这些话语歧义的许多副语言社交线索都减弱了，甚至完全消失了。三组研究活动将：(1)调查消息创建者的语用意图与不同目标受众如何解释它们之间的不匹配，(2)开发技术来自动识别何时发生了语用误解并检测其对对话的影响，以及(3)开发界面工具来帮助预防或克服语用失败。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

This project will develop new ways of understanding miscommunication in social media and will design novel interventions to prevent or reduce misunderstandings. Online conversations often become increasingly hostile over time, resulting in disruptive behavior such as trolling, personal attacks, harassment, and bullying. Prior work has shown that in some cases these derailments can be traced back to ill-intentioned individuals and to social contagion. In other cases, however, disruptions may result from simple misunderstandings: readers may misconstrue the social intentions of the poster, concluding that a message is meant to be friendly or hostile or aggressive when actually the opposite was intended. This project will create a framework for understanding when and why social intentions are misunderstood, computational methods for automatically capturing the effects of such misperceptions on the trajectory and outcome of online conversations, and tools that might help prevent misunderstandings. The research combines natural language processing and computer-mediated communication expertise, in the context of social computing and human-computer interaction. Unlike other work that examines how the content of messages is misunderstood, this research aims to understand problems identifying the pragmatic force of a message, for example whether it is meant as a command or request, a joke, or a hostile remark. Such "pragmatic failures" are rooted in the distinction between the literal meaning of a message and its intended meaning, as well as in the varying propensity of readers with different sociocultural backgrounds to perceive one or the other. This phenomenon is especially problematic online, where many of the paralinguistic social cues people rely on offline to disambiguate such utterances are attenuated or even completely missing. Three sets of research activities will: (1) investigate mismatches between the message creator's pragmatic intentions and how they are interpreted by different target audiences, (2) develop techniques to automatically identify when pragmatic misunderstandings have occurred and to detect their effects on conversations, and (3) develop interface tools to help prevent or overcome pragmatic failures.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.