Syntactic measurement of governance networks from textual data, with application to water management plans.

This paper demonstrates an automated workflow for extracting network data from policy documents. We use natural language processing tools, part‐of‐speech tagging, and syntactic dependency parsing, to represent relationships between real‐world entities based on how they are described in text. Using a...

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Publicado en:Policy Studies Journal Vol. 52; no. 4; pp. 941 - 955
Autores principales: Zufall, Elise, Scott, Tyler A.
Formato: Artículo
Publicado: Wiley-Blackwell Nov2024
Materias:
Acceso en línea:Ver este registro en EBSCOhost
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        atl: Syntactic measurement of governance networks from textual data, with application to water management plans.
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        au:
          Zufall, Elise
          Scott, Tyler A.
        affil:
          Center for Environmental Policy and Behavior, University of California, Davis California,, USA
          Department of Environmental Science and Policy, University of California, Davis California,, USA
      su:
        Network governance
        Public administration
        Natural language processing
        Groundwater management
        Water management
      sug:
        subj:
          Network governance
          Public administration
          Other General Government Support
          Natural language processing
          Groundwater management
          Water management
      keyword:
        automation
        governance networks
        groundwater management
        network analysis
        NLP
        procesamiento del lenguaje natural
        redes de gobernanza
        texto como datos
        文本即数据
        治理网络
        自然语言处理
        automation
        governance networks
        groundwater management
        network analysis
        NLP
        procesamiento del lenguaje natural
        redes de gobernanza
        texto como datos
        文本即数据
        治理网络
        自然语言处理
      ab: This paper demonstrates an automated workflow for extracting network data from policy documents. We use natural language processing tools, part‐of‐speech tagging, and syntactic dependency parsing, to represent relationships between real‐world entities based on how they are described in text. Using a corpus of regional groundwater management plans, we demonstrate unique graph motifs created through parsing syntactic relationships and how document‐level syntax can be aggregated to develop large‐scale graphs. This approach complements and extends existing methods in public management and governance research by (1) expanding the feasible geographic and temporal scope of data collection and (2) allowing for customized representations of governance systems to fit different research applications, particularly by creating graphs with many different node and edge types. We conclude by reflecting on the challenges, limitations, and future directions of automated, text‐based methods for governance research.
      pubtype: Academic Journal
      doctype: Article
      src: R
    language: English
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