Bibliometric Analysis and Literature Review of Big Data Research Fields using Publish or Perish and VOSviewer - Fahrudin, Tresna Maulana (Future Science, 2023)
The evolution of data develops from homogeneous data to heterogeneous data, resulting in the emergence of structured, semi-structured, and unstructured data. The current trend in research methods is not only based on qualitative methods but is shifting towards quantitative with the spread of social media data which can be analyzed using Big Data technology. Explore Big Data ideas and research requires supporting software to collect bibliography data and literature review. Therefore, the research implements bibliometric analysis and literature review in Big Data fields using Publish or Perish to collect bibliography data and using VOSviewer to visualize bibliometric networks. The results of research using keywords containing the term Big Data and Hadoop software produced around 200 titles of scientific articles from the Scopus Journal to produce bibliography data visualizations based on network visualization, overlay visualization, and density visualization. Network visualization displays Big Data research clusters in the fields of data mining, health, education, data security, sentiment analysis, spatial temporal, machine learning, and blockchain. Literature reviews are carried out by identifying problem objects, data samples, methods, and tools, as well as evaluating of the scientific articles collected. In future research, further bibliometric analysis is needed using data from scientific article authors and looking at the author's connection to their research field.