Lesnikowski, A, Belfer, E, Rodman, E et al. (5 more authors) (2019) Frontiers in data analytics for adaptation research: Topic modeling. Wiley Interdisciplinary Reviews: Climate Change, 10 (3). e576. ISSN 1757-7780
Abstract
Rapid growth over the past two decades in digitized textual information represents untapped potential for methodological innovations in the adaptation governance literature that draw on machine learning approaches already being applied in other areas of computational social sciences. This Focus Article explores the potential for text mining techniques, specifically topic modeling, to leverage this data for large‐scale analysis of the content of adaptation policy documents. We provide an overview of the assumptions and procedures that underlie the use of topic modeling, and discuss key areas in the adaptation governance literature where topic modeling could provide valuable insights. We demonstrate the diversity of potential applications for topic modeling with two examples that examine: (a) how adaptation is being talked about by political leaders in United Nations Framework Convention on Climate Change; and (b) how adaptation is being discussed by decision‐makers and public administrators in Canadian municipalities using documents collected from 25 city council archives.
This article is categorized under:
Vulnerability and Adaptation to Climate Change > Institutions for Adaptation
Metadata
Item Type: | Article |
---|---|
Authors/Creators: |
|
Copyright, Publisher and Additional Information: | © 2019 Wiley Periodicals, Inc. This is the peer reviewed version of the following article: Lesnikowski, A, Belfer, E, Rodman, E et al. (5 more authors) (2019) Frontiers in data analytics for adaptation research: Topic modeling. Wiley Interdisciplinary Reviews: Climate Change, 10 (3). e576. ISSN 1757-7780, which has been published in final form at https://doi.org/10.1002/wcc.576. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions. |
Keywords: | climate change adaptation; governance; policy; quantitative text analysis; topic models |
Dates: |
|
Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Environment (Leeds) > School of Earth and Environment (Leeds) > Sustainability Research Institute (SRI) (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 11 Jan 2021 14:42 |
Last Modified: | 11 Jan 2021 14:42 |
Status: | Published |
Publisher: | Wiley |
Identification Number: | 10.1002/wcc.576 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:169838 |