RAPID: Immediate Social Media Data Collection in Key Election Contexts

选举对网络空间的安全性和可信度构成了重大挑战。选举期间的协调信息行动和在线政治暴力组织威胁着许多民主国家的完整性。我们缺乏可比较的跨国数据来帮助我们了解这些威胁是如何在各国之间运作的，以及政治制度、网络基础设施和社会经济背景是如何形成这些威胁的。我们也缺乏候选人社交媒体行为的全面数据。这个项目将极大地增加学者对选举候选人社交媒体行为以及选民如何回应这种行为的数据的访问。这项工作将允许目前不可能的调查，包括虚假信息在竞选期间如何在网上传播，以及这些信息如何影响面临不同民主扩张阶段的一系列政治国家的普通选民的信仰。这些数据还可以告知有意确保选举安全的政府，并可以帮助社交媒体公司了解他们的平台在竞选期间是如何使用的。这个项目的重点是为学者建立一个数据资源，从社交媒体数据收集围绕即将到来的选举在两极分化，民主化和其他相对不稳定的背景下。研究组根据民主主义、两极化、稳定性、网络基础设施等客观标准，有目的地对收集的候选人社交媒体（sns）数据的选举背景进行抽样。在所有这些背景下，研究团队正在汇编社交媒体候选人数据，包括候选人（公共）社交媒体账户，公开可用的候选人背景特征，以及捕获国家，选举和席位背景的其他变量。在其中三种情况下，研究小组正在对选民进行调查，收集选民获取候选人在线信息的能力、选民对候选人社交媒体活动的态度、候选人通过数字网络动员线下政治活动（包括选举暴力）的程度、政治家利用在线平台传播虚假信息的普遍和有效程度等方面的数据。以及选民在他们的背景下对政治网络空间安全性和稳定性的看法。研究团队正在为政治学、公共政策和网络安全领域的研究生开发网络研讨会系列的培训，以鼓励利用这些数据进行多学科研究。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。

Elections pose a critical challenge to the security and trustworthiness of cyberspace. Coordinated information operations and online organization of political violence during elections threaten the integrity of a wide range of democratic countries. We lack comparable cross-national data that can help us to understand how these threats operate across countries, and how political institutions, cyber-infrastructure, and socio-economic context shape such threats. We also lack comprehensive data about candidate social media behavior. This project will dramatically increase scholars' access to data on electoral candidates' social media behavior and how voters respond to this behavior. This work will allow currently impossible investigations of how false information travels online during electoral campaigns and how such information affects beliefs of average voters across a range of polities facing different stages of democratic expansion. These data can also inform governments interested in securing their elections and can assist social media firms in understanding how their platforms are used during campaigns.This project is focused on building a data resource for scholars from social media data collection surrounding upcoming elections in polarized, democratizing, and otherwise relatively unstable contexts. The research team is purposively sampling election contexts of candidate social media data collection that meet objective criteria based on their level of democracy, polarization, stability, and cyber infrastructure. Across all of these contexts, the research team is compiling social media candidate data, including candidate (public) social media accounts, publicly available candidate background characteristics, and other variables capturing the national, election, and seat(s) context. In three of these contexts, the research team is executing a survey among voters, collecting data on voters' ability to access candidates' online messages, voters' attitudes towards candidates' social media activity, the extent to which candidates mobilize offline political activity (including election violence) through digital networks, how commonly and effectively politicians spread disinformation using online platforms, and voters' perceptions of the security and stability of political cyberspace in their context. The research team is developing training in the form of webinar series for graduate students in political science, public policy, and cybersecurity to encourage multi-disciplinary research using the data.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.