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

被引:0
|
作者
Taboada-Villamarin, Alba [1 ]
Torres-Albero, Cristobal [1 ]
机构
[1] Autonomous Univ Madrid, Dept Sociol, Madrid 28049, Spain
来源
SOCIAL SCIENCES-BASEL | 2024年 / 13卷 / 02期
关键词
COVID-19; literature review; machine learning;
D O I
10.3390/socsci13020078
中图分类号
C [社会科学总论];
学科分类号
03 ; 0303 ;
摘要
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.
引用
收藏
页数:18
相关论文
共 50 条
  • [41] The evolution of Airbnb research: A systematic literature review using structural topic modeling
    Ding, Kai
    Niu, Yue
    Choo, Wei Chong
    HELIYON, 2023, 9 (06)
  • [42] A systematic literature review on humanitarian logistics using network analysis and topic modeling
    Kim, Jin Ju
    Jang, Hyunmi
    Roh, Saeyeon
    ASIAN JOURNAL OF SHIPPING AND LOGISTICS, 2022, 38 (04): : 263 - 278
  • [43] Changes in Digital Communication During the COVID-19 Global Pandemic: Implications for Digital Inequality and Future Research
    Nguyen, Minh Hao
    Gruber, Jonathan
    Fuchs, Jaelle
    Marler, Will
    Hunsaker, Amanda
    Hargittai, Eszter
    SOCIAL MEDIA + SOCIETY, 2020, 6 (03):
  • [44] Social Media Communication about HPV Vaccine in China: A Study Using Topic Modeling and Survey
    Jiang, Shaohai
    Wang, Pianpian
    Liu, Piper Liping
    Ngien, Annabel
    Wu, Xingtong
    HEALTH COMMUNICATION, 2023, 38 (05) : 935 - 946
  • [45] Exploring Public Emotions on Obesity During the COVID-19Pandemic Using Sentiment Analysis and Topic Modeling:Cross-Sectional Study
    Correia, Jorge Cesar
    Ahmad, Sarmad Shaharyar
    Waqas, Ahmed
    Meraj, Hafsa
    Pataky, Zoltan
    JOURNAL OF MEDICAL INTERNET RESEARCH, 2024, 26
  • [46] Discovering Latent Topics of Digital Technologies From Venture Activities Using Structural Topic Modeling
    Chae, Bongsug
    Olson, David L.
    IEEE TRANSACTIONS ON COMPUTATIONAL SOCIAL SYSTEMS, 2021, 8 (06): : 1438 - 1449
  • [47] Facilitating Communication in the Academic Environment During the Pandemic Using TeamSTEPPS Tools
    Cooke, Marcia
    Riddell, Deborah J.
    NURSE EDUCATOR, 2021, 46 (04) : 198 - 199
  • [48] Digital technology use during COVID-19 pandemic: A rapid review
    Vargo, Deedra
    Zhu, Lin
    Benwell, Briana
    Yan, Zheng
    HUMAN BEHAVIOR AND EMERGING TECHNOLOGIES, 2021, 3 (01) : 13 - 24
  • [49] News Coverage of Face Masks in Australia During the Early COVID-19 Pandemic: Topic Modeling Study
    Dasgupta, Pritam
    Amin, Janaki
    Paris, Cecile
    MacIntyre, C. Raina
    JMIR INFODEMIOLOGY, 2023, 3 (01):
  • [50] Deep Learning-based Sentiment Analysis and Topic Modeling on Tourism During Covid-19 Pandemic
    Mishra, Ram Krishn
    Urolagin, Siddhaling
    Jothi, J. Angel Arul
    Neogi, Ashwin Sanjay
    Nawaz, Nishad
    FRONTIERS IN COMPUTER SCIENCE, 2021, 3