Da Young Ju
Impact in
- Artificial Intelligence top 10%
- Topic Modeling
- Natural Language Processing Techniques
- AI in Service Interactions
- Text Readability and Simplification
- Human-Computer Interaction top 10%
Papers in
-
- Human-Automation Interaction and Safety 6
- Social Robot Interaction and HRI 6
- Safety Warnings and Signage 3
-
- AI in Service Interactions 4
- Co-authors
- Jung Min Lee (5 shared papers)Cynthia Gao (1 shared paper)Peng‐Jen Chen (1 shared paper)Naman Goyal (1 shared paper)Vishrav Chaudhary (1 shared paper)Angela Fan (1 shared paper)Marc’Aurelio Ranzato (1 shared paper)Francisco Guzmán (1 shared paper)
- Journals
- Electronics (4 papers)Sensors (2 papers)Behaviour and Information Technology (1 paper)International Journal of Automotive Technology (1 paper)International Journal of Environmental Research and Public Health (1 paper)
- Partner nations
- South KoreaChinaUnited States
In The Last Decade
Da Young Ju
37 papers receiving 348 citations
Peers
Comparison fields: 5 of 76
- Artificial Intelligence 193
- Human-Computer Interaction 29
- Social Psychology 72
- Health Informatics 4
- Information Systems and Management 19
Countries citing papers authored by Da Young Ju
This map shows the geographic impact of Da Young Ju'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 Da Young Ju with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Da Young Ju more than expected).
Fields of papers citing papers by Da Young Ju
This network shows the impact of papers produced by Da Young Ju. 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 Da Young Ju. The network helps show where Da Young Ju may publish in the future.
Co-authors
The 25 scholars most cited alongside Da Young Ju, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 41 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2022 | 108 | |
| 2 | 2021 | 45 | |
| 3 | 2018 | 38 | |
| 4 | 2020 | 24 | |
| 5 | 2020 | 12 | |
| 6 | 2018 | 11 | |
| 7 | 2018 | 11 | |
| 8 | 2021 | 10 | |
| 9 | 2019 | 10 | |
| 10 | 2023 | 8 | |
| 11 | 2015 | 7 | |
| 12 | 2019 | 7 | |
| 13 | 2020 | 7 | |
| 14 | 2018 | 6 | |
| 15 | 2015 | 6 | |
| 16 | 2013 | 6 | |
| 17 | 2016 | 5 | |
| 18 | 2023 | 5 | |
| 19 | 2021 | 5 | |
| 20 | 2018 | 5 |
About Da Young Ju
Da Young Ju is a scholar working on Social Psychology, Artificial Intelligence, Human-Computer Interaction, Automotive Engineering and Information Systems, having authored 41 papers that have together received 375 indexed citations. Recurring topics across this work include Human-Automation Interaction and Safety (6 papers), Social Robot Interaction and HRI (6 papers), Technology Use by Older Adults (4 papers), AI in Service Interactions (4 papers), Advanced Malware Detection Techniques (3 papers), Innovation in Digital Healthcare Systems (3 papers), Safety Warnings and Signage (3 papers) and Robotics and Sensor-Based Localization (2 papers). The work is most often cited by research in Artificial Intelligence (193 citations), Human-Computer Interaction (29 citations), Social Psychology (72 citations), Health Informatics (4 citations) and Information Systems and Management (19 citations). Da Young Ju has collaborated with scholars based in South Korea, China and United States. Frequent co-authors include Jung Min Lee, Cynthia Gao, Peng‐Jen Chen, Naman Goyal, Vishrav Chaudhary, Angela Fan, Marc’Aurelio Ranzato, Francisco Guzmán, Guillaume Wenzek and Jason Weston. Their work appears in journals such as Electronics, Sensors, Behaviour and Information Technology, International Journal of Automotive Technology and International Journal of Environmental Research and Public Health.
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.