Unlocking Environmental Narratives: Towards Understanding Human Environment Interactions through Computational Text Analysis

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ISBN 10: 1911529560 / ISBN 13: 9781911529569

Editore: Ubiquity Press Ltd, 2022

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Unlocking Environmental Narratives: Towards Understanding Human Environment Interactions through Computational Text Analysis This book is in very good condition and will be shipped within 24 hours of ordering. The cover may have some limited signs of wear but the pages are clean, intact and the spine remains undamaged. This book has clearly been well maintained and looked after thus far. Money back guarantee if you are not satisfied. See all our books here, order more than 1 book and get discounted shipping. .

Codice articolo 7719-9781911529569

Dati bibliografici

• Titolo: Unlocking Environmental Narratives: Towards Understanding Human Environment Interactions through Computational Text Analysis
• Editore: Ubiquity Press Ltd
• Data di pubblicazione: 2022
• Lingua: Inglese
• ISBN 10: 1911529560
• ISBN 13: 9781911529569
• Rilegatura: paperback
• Condizione: Very Good

Descrizione articolo

Riassunto

Understanding the role of humans in environmental change is one of the most pressing challenges of the 21st century. Environmental narratives - written texts with a focus on the environment - offer rich material capturing relationships between people and surroundings. We take advantage of two key opportunities for their computational analysis: massive growth in the availability of digitised contemporary and historical sources, and parallel advances in the computational analysis of natural language. We open by introducing interdisciplinary research questions related to the environment and amenable to analysis through written sources. The reader is then introduced to potential collections of narratives including newspapers, travel diaries, policy documents, scientific proposals and even fiction. We demonstrate the application of a range of approaches to analysing natural language computationally, introducing key ideas through worked examples, and providing access to the sources analysed and accompanying code. The second part of the book is centred around case studies, each applying computational analysis to some aspect of environmental narrative. Themes include the use of language to describe narratives about glaciers, urban gentrification, diversity and writing about nature and ways in which locations are conceptualised and described in nature writing. We close by reviewing the approaches taken, and presenting an interdisciplinary research agenda for future work. The book is designed to be of interest to newcomers to the field and experienced researchers, and set out in a way that it can be used as an accompanying text for graduate level courses in, for example, geography, environmental history or the digital humanities.

Informazioni sugli autori

Ross Purves is a professor of Geographic Information Science at the Department of Geography, University of Zurich. His research aims to address societally relevant research questions, with the fundamental aim of making theoretical, thematic and methodological contributions to Geographic Information Science. He is particularly interested in developing methods and answering questions through the use of unstructured information, often in the form of text.

Olga Koblet is a former postdoctoral researcher at the Geocomputation Group of the University of Zurich. Her focus lies in the use of unstructured text to better understand landscape and landscape perception. In particular, she has worked on new approaches to extracting descriptions of perception from unstructured text and linking these to landscape character assessment.

Benjamin Adams is an Associate Professor of Computer Science at the University of Canterbury in New Zealand. His expertise lies in the development and application of information retrieval and machine learning algorithms that aid the collection, management, analysis, and use of large spatial data sets to better support decision-making in complex environments. A key driver of his research is the goal of developing computational methods that can translate unstructured and semi-structured data that are created initially for human communication, such as crowdsourced social media and other natural language text and images, into forms that aid geographic problem solving.