Jamin Shin

1000 citations
16 papers · 359 · h-index 8

Impact in

Papers in

Journals
Korean Journal of Food Preservation (1 paper)Rare & Special e-Zone (The Hong Kong University of Science and Technology) (4 papers)Findings of the Association for Computational Linguistics: ACL 2022 (1 paper)Educational Data Mining (1 paper)

In The Last Decade

Jamin Shin

16 papers receiving 346 citations

Peers

Jamin Shin
Comparison fields: 5 of 57
  • Artificial Intelligence 273
  • Health Informatics 8
  • Applied Psychology 17
  • Experimental and Cognitive Psychology 32
  • Social Psychology 48
Replace Tulika Saha with:
Tulika Saha India
Justyna Sarzyńska‐Wawer Poland
Chujie Zheng China
Su‐Youn Yoon United States
Luca Soldaini United States
Wanling Cai Hong Kong
Bernd Kiefer Germany
Sophie Rosset France
Matthias Kraus Germany
Esaú Villatoro-Tello Mexico
Jamin Shin relative to Tulika Saha India Tulika Saha's profile →
Citations per field
00.5×7.3×
Tulika Saha · 1×
Citations per year

Countries citing papers authored by Jamin Shin

Since Specialization
Citations

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

Fields of papers citing papers by Jamin Shin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

16 of 16 papers shown
#Work
1 2019111
2 202082
3 202443
4 202030
5 202322
6 202216
7 202415
8 202413
9 20197
10 20206
11 20236
12 20223
13
Tracing Knowledge for Tracing Dropouts: Multi-Task Training for Study Session Dropout Prediction
20212
14
Understanding the Shades of Sexism in Popular TV Series
20191
15 20221
16
Low-Rank Matrix Factorization of LSTM as Effective Model Compression
20181

About Jamin Shin

Jamin Shin is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Information Systems, Statistical and Nonlinear Physics and Information Systems and Management, having authored 16 papers that have together received 359 indexed citations. Recurring topics across this work include Topic Modeling (8 papers), Natural Language Processing Techniques (5 papers), Sentiment Analysis and Opinion Mining (2 papers), Speech Recognition and Synthesis (2 papers), Multimodal Machine Learning Applications (1 paper), Intelligent Tutoring Systems and Adaptive Learning (1 paper), Media, Gender, and Advertising (1 paper) and Cassava research and cyanide (1 paper). The work is most often cited by research in Artificial Intelligence (273 citations), Health Informatics (8 citations), Applied Psychology (17 citations), Experimental and Cognitive Psychology (32 citations) and Social Psychology (48 citations). Jamin Shin has collaborated with scholars based in Hong Kong, South Korea and United States. Frequent co-authors include Pascale Fung, Peng Xu, Zhaojiang Lin, Andrea Madotto, Zihan Liu, Genta Indra Winata, Juho Kim, Young‐Ho Kim, Minjoon Seo and Joel Jang. Their work appears in journals such as Korean Journal of Food Preservation, Rare & Special e-Zone (The Hong Kong University of Science and Technology), Findings of the Association for Computational Linguistics: ACL 2022 and Educational Data Mining.

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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