Councils in Action: Automating the Curation of Municipal Governance Data for Research

TL;DR

This paper introduces the Council Data Project (CDP), an open-source platform that automates the collection and analysis of municipal governance data using speech-to-text and NLP, enabling comparative research and insights into government performance.

Contribution

The paper presents the CDP infrastructure for assembling reliable municipal governance data and demonstrates its application through exploratory analysis of three municipalities.

Findings

CDP enables reliable comparative municipal data collection

Analysis reveals governance performance trends over time

Future work includes machine learning for enhanced data annotation

Abstract

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.