Convergence and Divergence in Renewable Energy Frames Across the U.S. States: Semantic Topic Modeling on U.S. States’ Renewable Portfolio Standards

IF 0.5 4区 管理学 Q4 POLITICAL SCIENCE
Junseop Shim, Chang-Gyu Kwak
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引用次数: 0

Abstract

This study examined diversity and similarity of orientations for renewable energy policies across US states through frame analysis based on semantic topic modeling technique. More specifically, it analyzed Renewable Portfolio Standard (RPS) bills of 29 RPS adopted states. Latent Dirichlet Allocation (LDA) modeling for semantic topic analysis was applied to explore hidden meanings within text bills, as well as shared patterns of the meanings among states, by utilizing latent information of nested topic. It found two major themes of the definition of eligible renewables and implementation mechanisms, underlying the states’ RPSs substantially contributed to framing each state’s renewable energy policies. In accordance with the state’s energy situation and socio-economic interests in renewable energy, however, states’ frames for defining eligible renewables and for building implementation and compliance mechanisms differed substantially.
美国各州可再生能源框架的趋同与分化:基于美国各州可再生能源投资组合标准的语义主题建模
本研究通过基于语义主题建模技术的框架分析,考察了美国各州可再生能源政策取向的多样性和相似性。更具体地说,它分析了29个采用可再生能源投资组合标准(RPS)的州的法案。利用嵌套主题的潜在信息,将潜在狄利克雷分配(Latent Dirichlet Allocation, LDA)建模应用于语义主题分析,探索文本账单中隐藏的含义,以及状态间含义的共享模式。它发现了两个主要主题,即定义合格的可再生能源和实施机制,这是各州RPSs的基础,对制定各州的可再生能源政策做出了重大贡献。然而,根据各州的能源状况和可再生能源的社会经济利益,各州定义合格可再生能源的框架以及建立实施和合规机制的框架存在很大差异。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
1.10
自引率
25.00%
发文量
31
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