标题： 2022年美国中期选举中转发协调的结构和上下文 显示英文标题

标题： Structure and Context of Retweet Coordination in the 2022 U.S. Midterm Elections

摘要： 检测通信网络中的协调活动能力是一个持续的挑战。 先前的方法强调将任何超过特定相似性阈值的活动视为协调活动。 然而，确定这样的阈值通常是任意的，并且很难与基层组织的行为区分开来。 在本文中，我们研究了一组围绕2022年美国中期选举收集的Twitter转发数据，使用了一个潜在共享空间模型，在该模型中，我们以k最近邻准则对关联网络的主要成分进行了阈值处理。 这种方法识别出在不同范围内的网络中具有不同作用的关联值分布，分布的形状表明了协调用户候选人的自然阈值位置。 我们发现协调候选人属于两个主要类别，一个涉及音乐奖项和韩国流行音乐或泰勒·斯威夫特的推广，另一个是参与政治动员的用户。 此外，潜在空间表明，通过使用适当的高阈值准则进行协调，不同协调群体之间存在共同的动机，尽管它们原本因协调而分散。 显示英文摘要

摘要： The ability to detect coordinated activity in communication networks is an ongoing challenge. Prior approaches emphasize considering any activity exceeding a specific threshold of similarity to be coordinated. However, identifying such a threshold is often arbitrary and can be difficult to distinguish from grassroots organized behavior. In this paper, we investigate a set of Twitter retweeting data collected around the 2022 US midterm elections, using a latent sharing-space model, in which we identify the main components of an association network, thresholded with a k-nearest neighbor criterion. This approach identifies a distribution of association values with different roles in the network at different ranges, where the shape of the distribution suggests a natural place to threshold for coordinated user candidates. We find coordination candidates belonging to two broad categories, one involving music awards and promotion of Korean pop or Taylor Swift, the other being users engaged in political mobilization. In addition, the latent space suggests common motivations for different coordinated groups otherwise fragmented by using an appropriately high threshold criterion for coordination.