{"title":"Convergence and Divergence in Renewable Energy Frames Across the U.S. States: Semantic Topic Modeling on U.S. States’ Renewable Portfolio Standards","authors":"Junseop Shim, Chang-Gyu Kwak","doi":"10.4335/21.2.267-295(2023)","DOIUrl":null,"url":null,"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.","PeriodicalId":51875,"journal":{"name":"Lex Localis-Journal of Local Self-Government","volume":"11 1","pages":""},"PeriodicalIF":0.5000,"publicationDate":"2023-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Lex Localis-Journal of Local Self-Government","FirstCategoryId":"91","ListUrlMain":"https://doi.org/10.4335/21.2.267-295(2023)","RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"POLITICAL SCIENCE","Score":null,"Total":0}
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.