An Insight into the State of Big Data Research: A Bibliometric Study of Scientific Publications

被引：5
作者：
Islam M.N. [1 ]
机构：
[1] School of Information Management and Institute of Government Data Resources, Nanjing University, Nanjing, Xianlin
来源：
Science and Technology Libraries | 2024年 / 43卷 / 01期
关键词：
Bibliometric analysis; big data; collaboration culture; RStudio; trends; VOSviewer; web of science;
D O I：
10.1080/0194262X.2023.2185919
中图分类号：
学科分类号：
摘要：
In the past few years, the field of big data has multiplied, with more academic papers written about it. This bibliometric research was done to look at and understand the trends regarding countries, organizations, authors, and keywords that are creating the most publications and citations in big data. This study was done to understand the current state of scientific publications in the field. The research used Web of Science (WoS) database information from 1993 to 2021. The study of 32,085 papers showed that, on average, each document has 14.7 citations and 3.46 citations per year. According to the results, the United States, China, and the United Kingdom have the most scholarly publications about big data. The Chinese Academy of Science, Harvard University, and Stanford University were the three most productive groups. When researching big data, most writers work together, and most terms are related to big data analytics, machine learning, and cloud computing. © 2023 The Author(s). Published with license by Taylor & Francis Group, LLC.
引用
收藏
页码：31 / 51
页数：20
相关论文
共 101 条
  • [1] Aboelmaged M., Mouakket S., Influencing models and determinants in big data analytics research: A bibliometric analysis, Information Processing & Management, 57, 4, (2020)
  • [2] Agusti M.A., Orta-Perez M., Big data and artificial intelligence in the fields of accounting and auditing: A bibliometric analysis, Spanish Journal of Finance and Accounting / Revista Española de Financiación y Contabilidad, pp. 1-27, (2022)
  • [3] Ahmad I., Ahmed G., Adeel Ali Shah S., Ahmed E., A decade of big data literature: Analysis of trends in light of bibliometrics, The Journal of Supercomputing, 76, 5, pp. 3555-3571, (2020)
  • [4] Akoka J., Comyn-Wattiau I., Laoufi N., Research on big data–a systematic mapping study, Computer Standards & Interfaces, 54, November, pp. 105-115, (2017)
  • [5] Alemany Oliver M., Vayre J.S., Big data and the future of knowledge production in marketing research: Ethics, digital traces, and abductive reasoning, Journal of Marketing Analytics, 3, 1, pp. 5-13, (2015)
  • [6] Al-Fuqaha A., Guizani M., Mohammadi M., Aledhari M., Ayyash M., Internet of Things: A Survey on Enabling Technologies, Protocols, and Applications, IEEE Communications Surveys & Tutorials, 17, 4, pp. 2347-2376, (2015)
  • [7] Ardito L., Scuotto V., Del Giudice M., Petruzzelli A.M., A bibliometric analysis of research on big data analytics for business and management, Management Decision, 57, 8, pp. 1993-2009, (2019)
  • [8] Aria M., Cuccurullo C., Bibliometrix: An R-Tool for comprehensive science mapping analysis, Journal of Informetrics, 11, 4, pp. 959-975, (2017)
  • [9] Arief N.N., Gustomo A., Analyzing the impact of big data and artificial intelligence on the communications profession: A case study on public relations (PR) practitioners in Indonesia, International Journal on Advanced Science, Engineering and Information Technology, 10, 3, pp. 1066-1071, (2020)
  • [10] Aykroyd R.G., Leiva V., Ruggeri F., Recent developments of control charts, identification of big data sources and future trends of current research, Technological Forecasting and Social Change, 144, July, pp. 221-232, (2019)
12345678910