Bibliometric Study on the Role of Big Data in the Science Revolution
DOI:
https://doi.org/10.71238/snnst.v2i01.67Keywords:
Big Data, Science Revolution, Bibliometric Analysis, Artificial Intelligence, Data ScienceAbstract
The rapid proliferation of big data has ushered in a transformative era in scientific research, often referred to as the data-driven or fourth paradigm of science. This study employs a bibliometric approach using VOSviewer to analyze the intellectual structure, thematic evolution, and interdisciplinary impact of big data in the context of the modern science revolution. Drawing from the Scopus database, we examined publications from 2000 to 2024, focusing on co-occurrence of keywords, citation networks, and temporal patterns. The findings reveal that big data serves as a central node connecting diverse domains such as artificial intelligence, data science, genomics, industrial automation, and social sciences. Temporal overlay analysis indicates a shift from early emphasis on data management and social computing toward recent trends in AI, deep learning, and industry 4.0. Density visualizations highlight concentrated scholarly attention on computational and biomedical applications, while ethical and social implications remain underrepresented. This study affirms that big data is not merely a technological tool but a transformative epistemological force reshaping the landscape of contemporary scientific inquiry.
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Copyright (c) 2025 Loso Judijanto, Diky Wardhani (Author)
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