分裂的国家？一种基于文本和投票的偏好亲和块检测的复合网络方法
Disunited Nations? A Multiplex Network Approach to Detecting Preference Affinity Blocs using Texts and Votes
摘要：
本文有助于一个新兴的文学，模型投票和文本串联，以更好地理解表达偏好的极化。它介绍了一种新的方法来估计偏好极化多维设置，如国际关系，在自然语言处理和网络科学文献的基础上的发展-即词嵌入，保留了人类语言的有价值的句法质量，和社区发现在多层网络，它定位密集连接的演员在多个，复杂的网络。我们发现，这些工具的就业在串联有助于更好地估计国家的外交政策偏好，在联合国投票和演讲所表达的超出了投票本身所允许的。这些位于亲和力集团的效用是通过应用程序证明在国际关系中的冲突发作，虽然这些工具将是所有学者面临的多维设置中的偏好和极化的测量感兴趣。
英文摘要：
This paper contributes to an emerging literature that models votes and text in tandem to better understand polarization of expressed preferences. It introduces a new approach to estimate preference polarization in multidimensional settings, such as international relations, based on developments in the natural language processing and network science literatures -- namely word embeddings, which retain valuable syntactical qualities of human language, and community detection in multilayer networks, which locates densely connected actors across multiple, complex networks. We find that the employment of these tools in tandem helps to better estimate states' foreign policy preferences expressed in UN votes and speeches beyond that permitted by votes alone. The utility of these located affinity blocs is demonstrated through an application to conflict onset in International Relations, though these tools will be of interest to all scholars faced with the measurement of preferences and polarization in multidimensional settings.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
