Bing Qin

177 papers and 5.7k indexed citations i.

About

Bing Qin is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Information Systems. According to data from OpenAlex, Bing Qin has authored 177 papers receiving a total of 5.7k indexed citations (citations by other indexed papers that have themselves been cited), including 144 papers in Artificial Intelligence, 28 papers in Computer Vision and Pattern Recognition and 26 papers in Information Systems. Recurrent topics in Bing Qin’s work include Topic Modeling (111 papers), Natural Language Processing Techniques (71 papers) and Sentiment Analysis and Opinion Mining (41 papers). Bing Qin is often cited by papers focused on Topic Modeling (111 papers), Natural Language Processing Techniques (71 papers) and Sentiment Analysis and Opinion Mining (41 papers). Bing Qin collaborates with scholars based in China, United States and Singapore. Bing Qin's co-authors include Duyu Tang, Ting Liu, Ting Liu, Ming Zhou, Xiaocheng Feng, Furu Wei, Nan Yang, Yanyan Zhao, Zhangyin Feng and Nan Duan and has published in prestigious journals such as Bioinformatics, PLoS ONE and Brain Research.

In The Last Decade

Co-authorship network of co-authors of Bing Qin i

Fields of papers citing papers by Bing Qin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Bing Qin. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Bing Qin. The network helps show where Bing Qin may publish in the future.

Countries citing papers authored by Bing Qin

Since Specialization
Citations

This map shows the geographic impact of Bing Qin's research. 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 Bing Qin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Bing Qin more than expected).

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.

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2025