Countries where authors publish in Big Data Mining and Analytics
Since Specialization
Citations
This map shows the geographic impact of research published in Big Data Mining and Analytics. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by papers published in Big Data Mining and Analytics with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Big Data Mining and Analytics more than expected).
Fields of papers published in Big Data Mining and Analytics
This network shows the impact of papers published in Big Data Mining and Analytics. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers published in Big Data Mining and Analytics.
About Big Data Mining and Analytics
The 351 papers published in Big Data Mining and Analytics in the last decades have received a total of 7k indexed citations . Papers published in Big Data Mining and Analytics usually cover Artificial Intelligence (123 papers), Computer Vision and Pattern Recognition (53 papers), Information Systems (52 papers), Health Informatics (4 papers) and Signal Processing (12 papers) specifically the topics of Advanced Graph Neural Networks (20 papers), Privacy-Preserving Technologies in Data (20 papers), Recommender Systems and Techniques (18 papers), Advanced Neural Network Applications (14 papers), Topic Modeling (14 papers), Cloud Computing and Resource Management (13 papers), Complex Network Analysis Techniques (12 papers) and Sentiment Analysis and Opinion Mining (12 papers). The most active scholars publishing in Big Data Mining and Analytics are Yan Zhu Yang, Hao Wang, Amanpreet Kaur Sandhu, Mourade Azrour, Yousef Farhaoui, Yi Feng Pan, Min Li, Zhipeng Cai, Maninder Singh and Azidine Guezzaz.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive
bibliographic database. While OpenAlex provides broad and valuable coverage of the global
research landscape, it—like all bibliographic datasets—has inherent limitations. These include
incomplete records, variations in author disambiguation, differences in journal indexing, and
delays in data updates. As a result, some metrics and network relationships displayed in
Rankless may not fully capture the entirety of a scholar's output or impact.