Bei Yu

76 papers receiving 1.9k citations

Peers

Bei Yu
Comparison fields: 5 of 165
  • General Social Sciences 94
  • Marketing 181
  • Artificial Intelligence 613
  • Information Systems and Management 132
  • Communication 122
Replace Ke Xu with:
Ke Xu China
George Paltoglou Greece
Xingyu Wang United States
Deborah G. Johnson United States
Edgar A. Whitley United Kingdom
Ahmed Abbasi United States
Xieling Chen Hong Kong
Gilad Mishne Netherlands
Matúš Medo Switzerland
Xiaodan Song United States
Bei Yu relative to Ke Xu China Ke Xu's profile →
Citations per field
00.5×4.1×
Ke Xu · 1×
Citations per year

Countries citing papers authored by Bei Yu

Since Specialization
Citations

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

Fields of papers citing papers by Bei Yu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Bei Yu, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Bei Yu Line = papers co-authored together Bei Yu links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20250
2 20250
3 20241
4 20230
5 20232
6 20222
7 20222
8 20227
9 202044
10 20193
11
An Evaluation of Information Extraction Tools for Identifying Health Claims in News Headlines
20183
12 201712
13
Function Words for Chinese Authorship Attribution
20126
14
EXPLORING THE RELATIONSHIP BETWEEN MOOD AND CREATIVITY IN ROCK LYRICS
20117
15 2011101
16
Classifying Business Marketing Messages on Facebook
201113
17
Proceedings of the 1st international CIKM workshop on Topic-sentiment analysis for mass opinion
20092
18 200838
19 200713
20
bFGF as a therapeutic target for chemosensitization in colorectal cancer.
20061

About Bei Yu

Bei Yu is a scholar working on General Social Sciences, Artificial Intelligence, Computer Science Applications, Health Informatics and Structural Biology, having authored 84 papers that have together received 2.0k indexed citations. Recurring topics across this work include Topic Modeling (13 papers), Advanced Text Analysis Techniques (10 papers), Sentiment Analysis and Opinion Mining (8 papers), Computational and Text Analysis Methods (6 papers), Digital Marketing and Social Media (6 papers), Misinformation and Its Impacts (5 papers), VLSI and FPGA Design Techniques (4 papers) and Ethics in Clinical Research (4 papers). The work is most often cited by research in General Social Sciences (94 citations), Marketing (181 citations), Artificial Intelligence (613 citations), Information Systems and Management (132 citations) and Communication (122 citations). Bei Yu has collaborated with scholars based in United States, China and Hong Kong. Frequent co-authors include Linchi Kwok, Stefan Kaufmann, Daniel Diermeier, Atulya Velivelli, ChengXiang Zhai, Jian Fang Li, Bingya Liu, Zheng Zhu, Min Yan and Flip Korn. Their work appears in journals such as Therapeutic Innovation & Regulatory Science, Proceedings of the American Society for Information Science and Technology, Clinical Pharmacology & Therapeutics, British Journal of Political Science and Journal of Endourology.

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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2026