论文标题
行动中的理事会：自动化市政治理数据的研究
Councils in Action: Automating the Curation of Municipal Governance Data for Research
论文作者
论文摘要
由于缺乏高质量的数据，对市政治理的大规模比较研究通常非常困难。但是，语音到文本算法和自然语言处理的最新进展使得更容易地收集和分析有关市政府的数据成为可能。在本文中，我们介绍了一个开源平台，理事会数据项目（CDP），以策划新的数据集，以研究市政治理。这项工作的贡献是两个方面：1。我们证明，CDP作为基础设施，可用于组装有关市政治理的可靠比较数据； 2。我们提供了三个市政当局的探索性分析，以展示如何使用CDP数据来了解市政政府随着时间的推移如何表现。最后，我们通过描述有关CDP和CDP研究的未来方向，例如开发用于说话者注释，大纲生成的机器学习模型以及改进的链接数据的指定实体识别。
Large scale comparative research into municipal governance is often prohibitively difficult due to a lack of high-quality data. But, recent advances in speech-to-text algorithms and natural language processing has made it possible to more easily collect and analyze data about municipal governments. In this paper, we introduce an open-source platform, the Council Data Project (CDP), to curate novel datasets for research into municipal governance. The contribution of this work is two-fold: 1. We demonstrate that CDP, as an infrastructure, can be used to assemble reliable comparative data on municipal governance; 2. We provide exploratory analysis of three municipalities to show how CDP data can be used to gain insight into how municipal governments perform over time. We conclude by describing future directions for research on and with CDP such as the development of machine learning models for speaker annotation, outline generation, and named entity recognition for improved linked data.
