Yi-Shin Chen

1.6k citations
82 papers · 917 · h-index 14

Impact in

Papers in

Yi-Shin Chen

77 papers receiving 872 citations

Peers

Yi-Shin Chen
Comparison fields: 5 of 127
  • Artificial Intelligence 352
  • Applied Psychology 42
  • Endocrinology 46
  • Statistical and Nonlinear Physics 98
  • Information Systems 148
Replace Muhammad Shoaib with:
Muhammad Shoaib Pakistan
Chih-Ya Shen Taiwan
Yunfei Long United Kingdom
Arkadiusz Stopczynski Denmark
Wen Dong United States
Sang Won Lee United States
Yaoyun Zhang United States
Sung-Hee Kim South Korea
Soomin Kim South Korea
Yi-Shin Chen relative to Muhammad Shoaib Pakistan Muhammad Shoaib's profile →
Citations per field
00.5×10×14×
Muhammad Shoaib · 1×
Citations per year

Countries citing papers authored by Yi-Shin Chen

Since Specialization
Citations

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

Fields of papers citing papers by Yi-Shin Chen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Yi-Shin Chen. 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 Yi-Shin Chen. The network helps show where Yi-Shin Chen may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 82 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2018170
2 200862
3 201753
4 202245
5 201738
6 200338
7 201629
8 202225
9 201424
10 201617
11 201616
12 202116
13 201816
14 202115
15 201613
16 202013
17 202213
18 201813
19 201912
20 202212

About Yi-Shin Chen

Yi-Shin Chen is a scholar working on Artificial Intelligence, Statistical and Nonlinear Physics, Information Systems, Signal Processing and Electrical and Electronic Engineering, having authored 82 papers that have together received 917 indexed citations. Recurring topics across this work include Complex Network Analysis Techniques (19 papers), Sentiment Analysis and Opinion Mining (15 papers), Advanced Text Analysis Techniques (15 papers), Recommender Systems and Techniques (7 papers), Data Management and Algorithms (7 papers), Mental Health via Writing (6 papers), Web Data Mining and Analysis (5 papers) and Spam and Phishing Detection (5 papers). The work is most often cited by research in Artificial Intelligence (352 citations), Applied Psychology (42 citations), Endocrinology (46 citations), Statistical and Nonlinear Physics (98 citations) and Information Systems (148 citations). Yi-Shin Chen has collaborated with scholars based in Taiwan, United States and Japan. Frequent co-authors include Elvis Saravia, Yen-Hao Huang, Junlin Wu, Cyrus Shahabi, Chun‐Hao Chang, Chih-Yu Wang, Hin‐chung Wong, Wann‐Neng Jane, Kuan‐Jiuh Lin and Yin‐Cheng Yen. Their work appears in journals such as Scientific Reports, Applied Sciences, Social Network Analysis and Mining, Applied Intelligence and IEEE Transactions on Systems Man and Cybernetics Systems.

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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