CRII: SaTC: Moderating Effects of Automation on Information Transmission in Social Forums

该项目旨在开发和部署一个信息准确性评估系统，以支持在线话语调节和人类对在线信息的理解。了解信息的性质可以帮助用户识别基本的产品和服务，甚至可能有助于告知民主参与。该项目将帮助个人用户在一个环境中导航，在这个环境中，他们的在线同行的观点可能很难解释，或者其他用户可能不清楚其他用户是人类还是秘密的社交机器人(例如，用于社交工程来获取个人信息)。该研究项目开发了识别社交机器人并评估它们对论坛上声明的立场的能力，以支持一个系统，该系统将提供对网络内容的自动准确性评估和分析，以支持论坛主持人。这些项目将阐明社交机器人在影响读者对信息的感知方面的使用，使人们意识到信息世界中自动化的危险，并最终支持对自动化攻击的警惕和预期。该项目旨在开发一个开源的、自动化的社会信息准确性评估系统，该系统能够支持在线话语环境中的用户导航，并最终支持用户导航。该系统将以检测社交机器人和评估社会支持为辅助重点，使其能够过滤掉隐藏的自治代理，同时评估他们在支持或拒绝内容声明中所扮演的角色。一个史无前例的真实性标注数据集，将在线内容和相关的读者评论与社交机器人标注整合在一起，将通过读者支持标注进行扩展和丰富。这些将被用来开发机器学习工具，这些工具可以表明1)用户作为人类评论者的真实性，2)他们对声明的立场，以便3)支持对他们讨论的内容的真实性的评估。将建立一个平台和服务器到服务器的应用程序来支持论坛主持的实施，除了公开展示总结的结果外，还将为主持人提供实时分析、警报和交互式可视仪表板。该奖项反映了NSF的法定使命，并已通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

This project aims to develop and deploy an information veracity evaluation system to support online discourse moderation and human comprehension of online information. Understanding information's nature can help users to identify essential products and services, and even potentially help to inform democratic participation. The project will help individual users navigate an environment where the views of their online peers may be difficult to interpret, or where it may not be clear whether other users are human or covert social bots (e.g., for social engineering to obtain personal information). The research project develops capacities for identifying social bots and evaluating their stances towards claims on forums to underpin a system that will provide automated veracity evaluation of web content and analysis to support forum moderators. These projects will shed light on the use of social bots at affecting reader perceptions of information, bringing awareness to dangers of automation in the infosphere and ultimately, support for vigilance and anticipation of automation attacks. This project aims to produce an open-source, automated social information veracity evaluation system that can support moderation of, and ultimately, user navigation in online discourse environments. This system will be developed with auxiliary foci on detecting social bots and evaluating social support, making it capable of filtering out covert autonomous agents while assessing their roles in the support or denial of content claims. A veracity-annotated dataset of unprecedented size that integrates online content and associated reader commentary with social bot annotations will be extended and enriched with reader support annotations. These will be used to develop machine learning tools that can indicate 1) users' authenticity as human commenters and 2) their stances towards claims, in order to 3) support the evaluation of their discussed content's veracity. A platform and server-to-server applications will be built to support implementation for forum moderation, providing moderators live analytics, alerts, and an interactive visual dashboard, in addition to a public display of summarized results.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.