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

Bibliographic Data

ID6330527
AuthorsElise Zufall (0000-0003-4179-1163, Center for Environmental Policy and Behavior University of California Davis California USA), Tyler Andrew Scott (0000-0002-4214-5895, Center for Environmental Policy and Behavior University of California Davis California USA, corresponding author)
Year2024
Volume52
Issue4
Pages941-954
Publication date2024-11-01
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenuePolicy Studies Journal (JOURNAL)
Journal identifiersISSN: 0190-292X • E-ISSN: 1541-0072
PublisherWiley (PUBLISHER • GB)
DOI10.1111/psj.12556
OpenAlexW4401218836
LanguageEN
References cited32

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

Business · Corporate governance · Natural language processing · Process management · Complex Systems and Decision Making · Computer Science · E-Government and Public Services · Public Policy and Administration Research · Artificial Intelligence · Finance

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