The ways in which environmental priorities are framed are varied and influenced by political forces. One technological advance--the proliferation of government open data portals (ODPs)--has the potential to improve governance through facilitating access to data. Yet it is also known that the data hosted on ODPs may simply reflect the goals and interests of multiple levels of political power. In this article, I use traditional statistical correlation and regression techniques along with newer natural language processing and machine learning algorithms to analyze the corpus of datasets hosted on government ODPs (total: 49,066) to extract patterns that relate scales of governance and political liberalism/conservatism to the priorities and meaning attached to environmental issues. I find that state-level and municipal-level ODPs host different categories of environmental datasets, with municipal-level ODPs generally hosting more datasets pertaining to services and amenities and state-level ODPs hosting more datasets pertaining to resource protection and extraction. Stronger trends were observed for the influences of political conservatism/liberalism among state-level ODPs than for municipal-level ODPs.

制定环境优先事项的方式各不相同，并受政治力量的影响。一项技术进步——政府开放数据门户 (ODP) 的激增——有可能通过促进数据访问来改善治理。然而，众所周知，ODP 上托管的数据可能只是反映了多层次政治权力的目标和利益。在本文中，我使用传统的统计相关性和回归技术以及较新的自然语言处理和机器学习算法来分析托管在政府 ODP 上的数据集语料库（总计：49,066），以提取与治理和政治自由主义/保守主义规模相关的模式环境问题的优先事项和意义。我发现州级和市级 ODP 托管不同类别的环境数据集，市级 ODP 通常托管更多与服务和便利设施相关的数据集，而州级 ODP 托管更多与资源保护和开采相关的数据集。观察到政治保守主义/自由主义对州级 ODP 的影响比对市级 ODP 的影响更强。