Unveiling the knowledge structure of technological forecasting and social change (1969-2020) through an NMF-based hierarchical topic model
Zhu, Lin and Cunningham, Scott W. (2022) Unveiling the knowledge structure of technological forecasting and social change (1969-2020) through an NMF-based hierarchical topic model. Technological Forecasting and Social Change, 174. 121277. ISSN 0040-1625 (https://doi.org/10.1016/j.techfore.2021.121277)
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Abstract
This article examines the knowledge structure of the journal Technology Forecasting and Social Change (TFSC) from its inception in 1969 until 2020. In this paper we argue that the structure of knowledge in the field of technological forecasting is more complex than a topic model -- a bag of words -- can in fact effectively reveal. Therefore we propose and demonstrate a hierarchical model that selectively combines topics at varying levels of generality. The resultant analysis, which is based on non-negative matrix factorization, reveals four distinct branches of technology forecasting work, composed of seven distinct topics. Each topic and branch are examined individually through a detailed examination of terms and keywords. Representative works and authors in each of the branches are also identified. The method enables the examination of the complex structure of knowledge in a scientific journal in a succinct representation. The resultant analysis can assist future researchers, enabling them to better position their work, and to better identify the key references across the various subject silos.
ORCID iDs
Zhu, Lin and Cunningham, Scott W. ORCID: https://orcid.org/0000-0001-7140-916X;-
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Item type: Article ID code: 78311 Dates: DateEvent31 January 2022Published25 October 2021Published Online16 September 2021AcceptedSubjects: Social Sciences > Industries. Land use. Labor > Management. Industrial Management
TechnologyDepartment: Faculty of Humanities and Social Sciences (HaSS) > Government and Public Policy > Politics Depositing user: Pure Administrator Date deposited: 28 Oct 2021 11:35 Last modified: 06 Oct 2024 00:37 URI: https://strathprints.strath.ac.uk/id/eprint/78311