Hye-Won Choi
Impact in
- Language and Linguistics top 2%
- Syntax, Semantics, Linguistic Variation
- Linguistics and Language top 5%
- Linguistic Variation and Morphology
Papers in
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- Speech and dialogue systems 2
- Natural Language Processing Techniques 2
- Sentiment Analysis and Opinion Mining 1
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- Spam and Phishing Detection 2
- Web Data Mining and Analysis 2
- Journals
- Expert Systems with Applications (1 paper)Second language Research (1 paper)IEEE Access (1 paper)Pattern Recognition Letters (1 paper)Rutgers University Community Repository (Rutgers University) (1 paper)
- Partner nations
- South Korea
In The Last Decade
Hye-Won Choi
9 papers receiving 275 citations
Peers
Comparison fields: 5 of 38
- Language and Linguistics 225
- Linguistics and Language 97
- Experimental and Cognitive Psychology 119
- Artificial Intelligence 143
- Anthropology 41
Countries citing papers authored by Hye-Won Choi
This map shows the geographic impact of Hye-Won Choi'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 Hye-Won Choi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hye-Won Choi more than expected).
Fields of papers citing papers by Hye-Won Choi
This network shows the impact of papers produced by Hye-Won Choi. 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 Hye-Won Choi. The network helps show where Hye-Won Choi may publish in the future.
Co-authors
The 2 scholars most cited alongside Hye-Won Choi, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 1996 | 220 | |
| 2 | 2001 | 41 | |
| 3 | 2022 | 35 | |
| 4 | 2021 | 29 | |
| 5 | Length and Order: A Corpus Study of Korean Dative-Accusative Construction | 2007 | 16 |
| 6 | Paradigm Leveling in American Korean | 2003 | 14 |
| 7 | 2021 | 14 | |
| 8 | 2022 | 3 | |
| 9 | 2021 | 3 | |
| 10 | Analyzing and Predicting Ordering Choices in Korean with a Logistic Regression Model | 2010 | 1 |
| 11 | Beyond Grammatical Weight | 2008 | 0 |
| 12 | Capturing Lexical Variance with a Mixed Model : Verb in Ordering Variation | 2010 | 0 |
About Hye-Won Choi
Hye-Won Choi is a scholar working on Artificial Intelligence, Information Systems, Language and Linguistics, Sociology and Political Science and Computer Vision and Pattern Recognition, having authored 12 papers that have together received 376 indexed citations. Recurring topics across this work include Misinformation and Its Impacts (3 papers), Spam and Phishing Detection (2 papers), Web Data Mining and Analysis (2 papers), Speech and dialogue systems (2 papers), Advanced Image and Video Retrieval Techniques (2 papers), Natural Language Processing Techniques (2 papers), Syntax, Semantics, Linguistic Variation (2 papers) and Sentiment Analysis and Opinion Mining (1 paper). The work is most often cited by research in Language and Linguistics (225 citations), Linguistics and Language (97 citations), Experimental and Cognitive Psychology (119 citations), Artificial Intelligence (143 citations) and Anthropology (41 citations). Hye-Won Choi has collaborated with scholars based in South Korea. Frequent co-authors include Youngjoong Ko and Bosung Kim. Their work appears in journals such as Expert Systems with Applications, Second language Research, IEEE Access, Pattern Recognition Letters and Rutgers University Community Repository (Rutgers University).
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.