Current status and future agenda of citizen journalism research: a computational analysis
Purpose This paper aims to provide a comprehensive overview of the current status and future research agenda of citizen journalism through a computational analysis lens. It explores how technological advancements and evolving media consumption patterns have shaped the rise of citizen journalism, democratizing news production via social media and digital technologies and impacting traditional journalism and societal discourse. Design/methodology/approach A bibliometric analysis was conducted on 1,325 peer-reviewed articles related to citizen journalism sourced from the Dimensions.ai database. The study used the Biblioshiny app of the bibliometrix software and VOSviewer for network visualization. The analysis examined publication trends, citation patterns, major contributors, influential journals and main research directions to map the intellectual landscape of citizen journalism research. Findings The analysis revealed significant growth in citizen journalism publications starting from 2004, with peak years in 2021–2023. Key researchers and journals were identified, highlighting both sustained and emerging contributions. Co-occurrence of keywords indicated a focus on qualitative methods and the credibility of citizen journalism. International collaboration varied, with robust intra-country publications in the USA and high intercountry collaboration rates in Austria and Australia. European and North American universities, particularly the University of Seville and the University of Vienna, were noted for their significant contributions. Originality/value To the best of the author’s knowledge, this study is one of the first to apply comprehensive bibliometric techniques to the field of citizen journalism, offering a quantitative assessment of global research trends.
Authors
- Kinshuk Pathak
Institutions
- Central University of Punjab (IN)
Publication Details
- Journal
- Global Knowledge Memory and Communication
- Published
- 2025-03-06
- DOI
- https://doi.org/10.1108/gkmc-06-2024-0343
- Primary Topic
- Computational and Text Analysis Methods
- Type
- article
- Field-Weighted Citation Impact
- 0.00