Bingkun Wang

821 citations
49 papers · 578 · h-index 15

Impact in

Papers in

    • Sentiment Analysis and Opinion Mining 12
    • Text and Document Classification Technologies 7
    • Advanced Text Analysis Techniques 5
    • Topic Modeling 4
    • 2D Materials and Applications 4
    • Graphene research and applications 4

Bingkun Wang

46 papers receiving 565 citations

Peers

Bingkun Wang
Comparison fields: 5 of 97
  • Artificial Intelligence 176
  • General Social Sciences 10
  • Information Systems 63
  • Materials Chemistry 122
  • Industrial and Manufacturing Engineering 25
Replace Tianen Chen with:
Tianen Chen China
JinYeong Bak South Korea
Jean-Jacques Girardot France
Wenqiang Li China
Shiyue Zhang China
Mohammadsepehr Karimiziarani United States
Yanli Liu China
Bingkun Wang relative to Tianen Chen China Tianen Chen's profile →
Citations per field
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Tianen Chen · 1×
Citations per year

Countries citing papers authored by Bingkun Wang

Since Specialization
Citations

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

Fields of papers citing papers by Bingkun Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Bingkun Wang, 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 Bingkun Wang Line = papers co-authored together Bingkun Wang links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 49 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201870
2 201845
3 202230
4 202429
5 201725
6 202123
7 202022
8 202321
9 201821
10 202221
11 202421
12 202220
13 201519
14 202317
15 202114
16 202413
17 202313
18 202212
19 202411
20 201911

About Bingkun Wang

Bingkun Wang is a scholar working on Artificial Intelligence, Materials Chemistry, Biomedical Engineering, Information Systems and Oceanography, having authored 49 papers that have together received 578 indexed citations. Recurring topics across this work include Sentiment Analysis and Opinion Mining (12 papers), Text and Document Classification Technologies (7 papers), Nanowire Synthesis and Applications (6 papers), Spam and Phishing Detection (5 papers), Advanced Text Analysis Techniques (5 papers), 2D Materials and Applications (4 papers), Topic Modeling (4 papers) and Graphene research and applications (4 papers). The work is most often cited by research in Artificial Intelligence (176 citations), General Social Sciences (10 citations), Information Systems (63 citations), Materials Chemistry (122 citations) and Industrial and Manufacturing Engineering (25 citations). Bingkun Wang has collaborated with scholars based in China, Malaysia and United States. Frequent co-authors include Shufeng Xiong, Donghong Ji, Yongfeng Huang, Xing Li, Li Ma, Bing Chen, Gang Wang, Weimin Mao, J. Fan and Guanglin Zhang. Their work appears in journals such as IEEE Electron Device Letters, Computational Intelligence and Neuroscience, Scientific Reports, Marine Environmental Research and Journal of Alloys and Compounds.

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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