Purpose: The purpose of this paper is to present a comprehensive analysis of the current status and development of the digital journalism field from 1987 to 2021 using the Dimensions database.Design/methodology/approach: Using the Dimensions.ai database, 1734 articles were identified through search strategies which were published from 1987 to 2021. The downloaded results were analysed using specific parameters with the help of bibliometric and science mapping tools: Biblioshiny, VOSviewer and CiteSpace. The key contributions of the present comprehensive bibliometric study of the digital journalism field can be seen in terms of the following aspects: (1) Publication analysis from the perspectives of publication growth, key journals, contributing authors, institutions and countries done through Biblioshiny package. (2) Citation network analysis from the perspective of co-citation structure of papers, authors, countries and institutions done through VOSviewer. (3) Timeline analysis and keywords burst detection to identify hotspots and research trends in digital journalism with the help of CiteSpace.Findings: The first paper with the keyword digital journalism was published in the year 1989. From 2011 onwards, there has been growth in digital journalism literature. The most popular journal in digital journalism studies is Digital Journalism, Journalism, Journalism Practice, Journalism Studies. Lewis, S.C. has contributed the most number of papers in digital journalism. Further, authors from the countries the USA, Spain, Brazil and UK have contributed immensely. The citation network of authors, institutions and countries contributing to digital journalism studies has also been explored in the study. Through burst analysis, hot topics in digital journalism were identified.Originality/value: The paper provides a complete overview of the growth of digital journalism literature published from 1987 to 2021. The originality of this work lies in the triangulation of Biblioshiny, VOSviewer and CiteSpace software to present various aspects of bibliometric study. Findings of the study can help the researchers to identify areas as well as journals, authors, institutions working actively in the field of digital journalism.

Fuzzy Sets and Systems is an area of computational intelligence, pioneered by Lotfi Zadeh over 50 years ago in a seminal paper in Information and Control. Fuzzy Sets (FSs) deal with uncertainty in our knowledge of a particular situation. Research and applications in FSs have grown steadily over 50 years. More recently, we have seen a growth in Type-2 Fuzzy Set (T2 FS) related papers, where T2 FSs are utilized to handle uncertainty in realworld problems. In this paper, we have used bibliometric methods to obtain a broad overview of the area of T2 FSs. This method analyzes information on the bibliographic details of published journal papers, which includes title, authors, author address, journals and citations, extracted from the Science and Social Science Citation Indices in the Web of Science (WoS) database for the last 20 years (1997-2017). We have compared the growth of publications in the field of FSs, and its subset T2 FSs, identified highly cited papers in T2 FSs, highly cited authors, key institutions, and main countries with researchers involved in T2 FS related research.

Purpose: The main purpose of this study is to explore and validate the question “whether altmetric mentions can predict citations to scholarly articles”. The paper attempts to explore the nature and degree of correlation between altmetrics (from ResearchGate and three social media platforms) and citations.Design/methodology/approach: A large size data sample of scholarly articles published from India for the year 2016 is obtained from the Web of Science database and the corresponding altmetric data are obtained from ResearchGate and three social media platforms (Twitter, Facebook and blog through Altmetric.com aggregator). Correlations are computed between early altmetric mentions and later citation counts, for data grouped in different disciplinary groups.Findings: Results show that the correlation between altmetric mentions and citation counts are positive, but weak. Correlations are relatively higher in the case of data from ResearchGate as compared to the data from the three social media platforms. Further, significant disciplinary differences are observed in the degree of correlations between altmetrics and citations.Research limitations/implications: The results support the idea that altmetrics do not necessarily reflect the same kind of impact as citations. However, articles that get higher altmetric attention early may actually have a slight citation advantage. Further, altmetrics from academic social networks like ResearchGate are more correlated with citations, as compared to social media platforms.Originality/value: The paper has novelty in two respects. First, it takes altmetric data for a window of about 1–1.5 years after the article publication and citation counts for a longer citation window of about 3–4 years after the publication of article. Second, it is one of the first studies to analyze data from the ResearchGate platform, a popular academic social network, to understand the type and degree of correlations.Peer review: The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-11-2019-0364