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© 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.

Abstract

New ideas are often born from connecting the dots. What new ideas have emerged among the two highly trending research topics of sustainability and social media? In this study, we present an empirical analysis of 762 published works that included the terms “sustainability” and “social media” in their abstracts. The bibliographic data, including abstracts, were collected from the Scopus database. In order to conduct the analysis, we used the Latent Dirichlet Allocation (LDA), an unsupervised machine learning algorithm to extract the latent topics from the large quantity of research abstracts without any manual adjustment. The 10 main topics identified from our analysis revealed topographical maps of research in the field. By measuring the variation of topic distributions over time, we identified hot topics (research trends that are becoming increasingly popular over time) and cold topics. Sustainable consumer behavior, Sustainable community and Sustainable tourism were identified as being hot topics, while Education for sustainability was identified as the only cold topic. By identifying current trends in social media and sustainability research, our findings lay a platform from which further studies may abound.

Details

Title
Tracing the Trends in Sustainability and Social Media Research Using Topic Modeling
Author
Lee, Jee Hoon 1   VIAFID ORCID Logo  ; Wood, Jacob 2 ; Kim, Jungsuk 3   VIAFID ORCID Logo 

 Department of Business Administration, Sejong University, Seoul 05006, Korea; [email protected] 
 JCU Singapore Business School, James Cook University Singapore, Singapore 387380, Singapore; [email protected] 
 Department of Economics, Sejong University, Seoul 05006, Korea 
First page
1269
Publication year
2021
Publication date
2021
Publisher
MDPI AG
e-ISSN
20711050
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2562208974
Copyright
© 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.