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Detecting the research structure and topic trends of social media using static and dynamic probabilistic topic models

Muhammad Inaam ul haq (Nanjing University of Science and Technology, Nanjing, China)
Qianmu Li (Nanjing University of Science and Technology, Nanjing, China)
Jun Hou (Nanjing Vocational University of Industry Technology, Nanjing, China)
Adnan Iftekhar (Wuhan University, Wuhan, China)

Aslib Journal of Information Management

ISSN: 2050-3806

Article publication date: 14 September 2022

Issue publication date: 23 March 2023

5096

Abstract

Purpose

A huge volume of published research articles is available on social media which evolves because of the rapid scientific advances and this paper aims to investigate the research structure of social media.

Design/methodology/approach

This study employs an integrated topic modeling and text mining-based approach on 30381 Scopus index titles, abstracts, and keywords published between 2006 and 2021. It combines analytical analysis of top-cited reviews with topic modeling as means of semantic validation. The output sequences of the dynamic model are further analyzed using the statistical techniques that facilitate the extraction of topic clusters, communities, and potential inter-topic research directions.

Findings

This paper brings into vision the research structure of social media in terms of topics, temporal topic evolutions, topic trends, emerging, fading, and consistent topics of this domain. It also traces various shifts in topic themes. The hot research topics are the application of the machine or deep learning towards social media in general, alcohol consumption in different regions and its impact, Social engagement and media platforms. Moreover, the consistent topics in both models include food management in disaster, health study of diverse age groups, and emerging topics include drug violence, analysis of social media news for misinformation, and problems of Internet addiction.

Originality/value

This study extends the existing topic modeling-based studies that analyze the social media literature from a specific disciplinary viewpoint. It focuses on semantic validations of topic-modeling output and correlations among the topics and also provides a two-stage cluster analysis of the topics.

Keywords

Acknowledgements

This work was supported by the major project of philosophy and social science research in colleges and universities of Jiangsu Province “Research on the Construction of Selective Compulsory Courses of Ideological and Political Science in Higher vocational Colleges” (2022SJZDSZ011) and the Research Project of Nanjing Polytechnic Institute (2020SKYJo3).

Citation

Inaam ul haq, M., Li, Q., Hou, J. and Iftekhar, A. (2023), "Detecting the research structure and topic trends of social media using static and dynamic probabilistic topic models", Aslib Journal of Information Management, Vol. 75 No. 2, pp. 215-245. https://doi.org/10.1108/AJIM-02-2022-0091

Publisher

:

Emerald Publishing Limited

Copyright © 2022, Emerald Publishing Limited

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