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Water relationships in the US southwest: characterizing water management networks using natural language processing

Murphy, J; Ozik, J; Collier, N; Altaweel, M; Lammers, R; Kliskey, A; Alessa, L; ... Williams, P; + view all (2014) Water relationships in the US southwest: characterizing water management networks using natural language processing. Water , 6 (6) 1601- 1641. 10.3390/w6061601. Green open access

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Abstract

Natural language processing (NLP) and named entity recognition (NER) techniques are applied to collections of newspaper articles from four cities in the U.S. Southwest. The results are used to generate a network of water management institutions that reflect public perceptions of water management and the structure of water management in these areas. This structure can be highly centralized or fragmented; in the latter case, multiple peer institutions exist that may cooperate or be in conflict. This is reflected in the public discourse of the water consumers in these areas and can, we contend, impact the potential responses of management agencies to challenges of water supply and quality and, in some cases, limit their effectiveness. Flagstaff, AZ, Tucson, AZ, Las Vegas, NV, and the Grand Valley, CO, are examined, including more than 110,000 articles from 2004–2012. Documents are scored by association with water topics, and phrases likely to be institutions are extracted via custom NLP and NER algorithms; those institutions associated with water-related documents are used to form networks via document co-location. The Grand Valley is shown to have a markedly different structure, which we contend reflects the different historical trajectory of its development and its current state, which includes multiple institutions of roughly equal scope and size. Overall, results demonstrate the utility of using NLP and NER methods presented here for understanding the structure and variation of water management systems.

Type: Article
Title: Water relationships in the US southwest: characterizing water management networks using natural language processing
Open access status: An open access version is available from UCL Discovery
DOI: 10.3390/w6061601
Publisher version: http://dx.doi.org/10.3390/w6061601
Language: English
Additional information: © 2014 by the authors; licensee MD PI, Basel, Switzerland. This arti cle is an open access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons .org/licenses/by/3.0/)
UCL classification: UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > UCL SLASH
UCL > Provost and Vice Provost Offices > UCL SLASH > Faculty of SandHS > Institute of Archaeology
UCL > Provost and Vice Provost Offices > UCL SLASH > Faculty of SandHS > Institute of Archaeology > Institute of Archaeology Gordon Square
URI: http://discovery.ucl.ac.uk/id/eprint/1430351
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