Bibliometric Analysis of the Journal of Big Data: Trends, Impact, and Future Directions

Abstract

The Journal of Big Data, a peer-reviewed publication since 2014, has played a pivotal role in the field of big data research by disseminating a total of 788 papers over its ten years of activity. Of these, 649 papers have garnered citations, with 46 receiving over 100 citations. The journal maintains an average of 37.13 citations per paper, with a higher average of 45.09 citations per cited paper, reflecting its significant impact. An h-index of 70 and a g-index of 158 further underscore its academic influence. The journal’s active year growth rate of 39.88% signifies its consistent expansion, while the average document age of 2.83 years indicates a focus on current developments. Collaborative research is a hallmark of the journal, evident in its 3.47 average authors per paper and 19.67% of papers with international co-authorships. The analysis of year-wise performance and citation trends offers insights into scholarly output and engagement. Visualizing collaborative relationships among authors highlights prominent nodes of interaction, revealing key contributors. Noteworthy institutions such as Florida Atlantic University, USA, and Bina Nusantara University, Indonesia, emerge in the landscape of research productivity. An exploration of keywords and their co-occurrence uncovers thematic clusters, ranging from big data technologies and deep learning to natural language processing and machine learning. In conclusion, the Journal of Big Data stands as a vital platform for disseminating impactful research in the dynamic realm of big data. Its comprehensive analysis emphasizes its academic influence through citation metrics, collaborative research, and thematic explorations. Through its decade-long journey, the journal has solidified its role in advancing the field and fostering global collaboration among researchers.