Digital Communication Studies during the Pandemic: A Sociological Review Using Topic Modeling Strategy

Alba Taboada-Villamarín () and Cristóbal Torres-Albero ()
Additional contact information
Alba Taboada-Villamarín: Department of Sociology, Autonomous University of Madrid, 28049 Madrid, Spain
Cristóbal Torres-Albero: Department of Sociology, Autonomous University of Madrid, 28049 Madrid, Spain

Social Sciences, 2024, vol. 13, issue 2, 1-18

Abstract: The health crisis triggered by COVID-19 has exerted a profound influence on both conventional communication methods and the manifestations of interaction within the virtual sphere. Gradually, studies on digital communication have taken on an increasingly prominent role in various social science disciplines that address determinants such as the crisis of misinformation or digital interaction in contemporary societies. This study aims to analyze the key research topics that sociology has addressed in relation to the pandemic, along with the level of innovation in the utilization of digital sources and analytical methodology. The analysis is grounded in the hypothesis that the effects of the pandemic have led the discipline of sociology to reassess and more fully integrate studies on digital communication. On this premise, a systematic review of studies sourced from the Web of Science (WoS) and Scopus databases was executed. Innovative computational methodologies were employed for the categorization of articles and the elucidation of principal research topics. Furthermore, this research scrutinized the principal digital platforms utilized in these investigations and assessed the extent of methodological innovation applied to data analysis. The outcomes unveiled a pronounced ascendancy in the prominence of communication studies during the pandemic. Nevertheless, it is noteworthy that the utilization of digital data sources in research remains surprisingly limited. This observation highlights a potential avenue for further exploration within the domain of sociological research, promising a more profound and contemporaneous comprehension of social phenomena amid times of crisis.

Keywords: COVID-19; literature review; machine learning (search for similar items in EconPapers)
JEL-codes: A B N P Y80 Z00 (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2076-0760/13/2/78/pdf (application/pdf)
https://www.mdpi.com/2076-0760/13/2/78/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jscscx:v:13:y:2024:i:2:p:78-:d:1326678

Access Statistics for this article

Social Sciences is currently edited by Ms. Yvonne Chu

More articles in Social Sciences from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().