HCC: Medium: Deterring objectionable behavior and fostering emergent norms in social media conversations

这项工作旨在建立一个理论模型，以理解规范的出现和维持，以阻止规则不由任何权威制定的自组织社交媒体空间中的令人反感的行为。令人反感的言论，如错误信息、仇恨言论和骚扰，在这些网络环境中普遍存在，这就提出了一个问题，即个人如何培养规范来阻止令人反感的言论。然而，尽管研究人员注意到社会规范对社交媒体和在线社区的影响，但现有的关于这些规范形成机制的理论工作侧重于促进合作的规范，而不是阻止不必要贡献的规范。该项目将有利于在线空间的公共话语，以及研究和教育成果，通过以下方式：(1)制定干预措施，帮助公民成为他们可能在社交媒体上遇到的错误信息、仇恨言论和骚扰的有效反对者；(2)开发一种新的研究工具，以连接个人和集体实验；(3)提供和传播理论模型，说明个人和集体观众如何回应不同领域对有问题内容的反对意见；(4)提高对反对意见的潜在认识，即使是出于善意，也可能在特定的观众条件下适得其反。这项研究的结果将是对遏制不良行为的紧急规范的理解的理论进步，以及一个内部和外部验证的多层次模型，建议在现实世界中部署的具体策略。本研究旨在通过多层次、多方法的探究来实现这些目标。它将测试不同的反对错误信息、仇恨言论和骚扰的方式在不同的观众集体条件和不同的社交媒体支持下的影响。该项目分为四个研究阶段：真实世界的观察、个人层面的实验、基于主体的模拟和集体层面的实验。然后是现场执行阶段。在观察阶段，它将从社交媒体上获取现实世界对攻击性言论的反对意见，并将其映射到理论空间中。在个体层面的实验阶段，它将使用一个新的模拟社交媒体环境来测试在观察阶段观察到的效应是否在个体层面上具有因果影响。基于代理的模拟阶段将使用个人层面的机制来大规模地模拟反对者和观众之间的互动。在集体实验阶段，研究将测试真实人群之间互动的集体动态是否与基于主体的模拟产生的动态相匹配。最后，在实地实施阶段，从研究中得出的基于证据的策略将构建可扩展的在线学习模块，以培训社交媒体用户在社交媒体上遇到话语冒犯时如何成为有效的反对者。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 work seeks to develop a theoretical model for understanding the emergence and maintenance of norms to deter objectionable behavior in self-organized social media spaces where rules are not set by any authority. Objectionable speech, such as misinformation, hate speech, and harassment, is prevalent in these online environments, which raises the question how individuals can foster norms to discourage objectionable speech. Yet while researchers note the influence of social norms within social media and online communities, existing theoretical work on the mechanisms through which such norms emerge focuses on norms promoting cooperation as opposed to norms that deter unwanted contributions. This project will benefit public discourse in online spaces, as well as research and educational outcomes, by: (1) Developing interventions that help citizens become effective objectors to the misinformation, hate speech and harassment they are likely to encounter on social media; (2) Developing a novel research tool for bridging individual and collective experimentation; (3) Providing and disseminating theoretical models of how individual and collective audiences respond to objections to problematic content in different domains, and (4) Raising awareness of the potential for objections, even if well-intentioned, to backfire in particular audience conditions. The result of this research will be a theoretical advancement in the understanding of emergent norms for the deterrence of unwanted behaviors as well as an internally and externally validated multi-level model recommending concrete strategies to be deployed in the real world.This research seeks to achieve these goals through a multi-level, multi-method inquiry. It will test the impact of different ways of objecting to misinformation, hate speech, and harassment under different collective conditions in the audience and different social media affordances. The project proceeds in four research phases: real world observation, individual-level experimentation, agent-based simulation, and collective-level experimentation. These are followed by a field implementation phase. In the observation phase, it will obtain real-world objections to offensive speech from social media and map these into a theoretical space. In the individual-level experimentation phase, it will use a novel simulated social media environment to test whether effects observed in the observational phase have causal influence at the individual level. The agent-based simulation phase will use the individual-level mechanisms to build simulations of interactions between objectors and audience members at scale. In the collective experimentation phase, the research will test whether the collective dynamics of interaction among real people match those produced by the agent-based simulation. Finally, in the field implementation phase, the evidence-based strategies derived from the research will build scalable online learning modules to train social media users on how to be effective objectors when encountering a discursive offense in social media.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.