Shi Feng

207 total papers · 2.6k total citations
80 papers, 1.1k citations indexed

About

Shi Feng is a scholar working on Artificial Intelligence, Information Systems and Computer Vision and Pattern Recognition. According to data from OpenAlex, Shi Feng has authored 80 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 59 papers in Artificial Intelligence, 16 papers in Information Systems and 12 papers in Computer Vision and Pattern Recognition. Recurrent topics in Shi Feng's work include Topic Modeling (32 papers), Sentiment Analysis and Opinion Mining (26 papers) and Text and Document Classification Technologies (15 papers). Shi Feng is often cited by papers focused on Topic Modeling (32 papers), Sentiment Analysis and Opinion Mining (26 papers) and Text and Document Classification Technologies (15 papers). Shi Feng collaborates with scholars based in China, United States and Singapore. Shi Feng's co-authors include Daling Wang, Yifei Zhang, Gábor Karsai, Aditya Agrawal, Xiaocui Yang, Ge Yu, Jonathan Sprinkle, Kaisong Song, Wei Gao and Yifei Zhang and has published in prestigious journals such as IEEE Transactions on Neural Networks and Learning Systems, IEEE Transactions on Knowledge and Data Engineering and Knowledge-Based Systems.

In The Last Decade

Shi Feng

68 papers receiving 988 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author						Papers	Cites
Shi Feng	837	271	233	189	62	80	1.1k
Derek Partridge	434 0.5×	118 0.4×	43 0.2×	86 0.5×	47 0.8×	71	799
Yuan Yao	416 0.5×	521 1.9×	162 0.7×	97 0.5×	145 2.3×	76	934
Nicolas Gold	249 0.3×	733 2.7×	531 2.3×	77 0.4×	195 3.1×	84	1.1k
Zhuo Zhang	311 0.4×	438 1.6×	139 0.6×	72 0.4×	234 3.8×	81	985
Hongji Yang	416 0.5×	736 2.7×	206 0.9×	97 0.5×	329 5.3×	147	1.2k
Andrea Corradini	610 0.7×	173 0.6×	323 1.4×	186 1.0×	139 2.2×	111	1.1k
Tianyi Zhang	522 0.6×	465 1.7×	208 0.9×	109 0.6×	147 2.4×	48	1.1k
Francesco Bergadano	501 0.6×	528 1.9×	61 0.3×	118 0.6×	196 3.2×	74	1.1k
Stephen MacNeil	388 0.5×	239 0.9×	81 0.3×	54 0.3×	33 0.5×	62	1.0k
Yuting Chen	248 0.3×	499 1.8×	553 2.4×	120 0.6×	205 3.3×	67	1.2k

Countries citing papers authored by Shi Feng

Since Specialization

Citations

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

Fields of papers citing papers by Shi Feng

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Shi Feng. 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 Shi Feng. The network helps show where Shi Feng may publish in the future.

Co-authorship network of co-authors of Shi Feng

This figure shows the co-authorship network connecting the top 25 collaborators of Shi Feng. A scholar is included among the top collaborators of Shi Feng based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Shi Feng. Shi Feng is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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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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