Jin Yea Jang
- Sociology and Political Science top 2%
- Artificial Intelligence top 2%
- Information Systems top 2%
- Communication top 5%
- Signal Processing top 5%
- Co-authors
- Svitlana VolkovaHannah RashkinEunsol ChoiYejin ChoiNathan O. HodasKyle ShafferKyungsik HanDongwon Lee
- Topics
- Misinformation and Its Impacts (7 papers)Speech and dialogue systems (6 papers)Social Media and Politics (5 papers)
- Journals
- ComputerEmpirical Methods in Natural Language ProcessingProceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
- Partner nations
- United StatesSouth Korea
In The Last Decade
Jin Yea Jang
16 papers receiving 875 citations
Hit Papers
Peers
Comparison fields: 5 of 55
- Sociology and Political Science 751
- Artificial Intelligence 530
- Information Systems 454
- Communication 112
- Signal Processing 108
Countries citing papers authored by Jin Yea Jang
This map shows the geographic impact of Jin Yea Jang'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 Jin Yea Jang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jin Yea Jang more than expected).
Fields of papers citing papers by Jin Yea Jang
This network shows the impact of papers produced by Jin Yea Jang. 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 Jin Yea Jang. The network helps show where Jin Yea Jang may publish in the future.
Co-authorship network of co-authors of Jin Yea Jang
This figure shows the co-authorship network connecting the top 25 collaborators of Jin Yea Jang. A scholar is included among the top collaborators of Jin Yea Jang based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Jin Yea Jang. Jin Yea Jang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 0 | |
| 3 | 1 | |
| 4 | 6 | |
| 5 | 10 | |
| 6 | 2 | |
| 7 | 8 | |
| 8 | 1 | |
| 9 | 36 | |
| 10 | 5 | |
| 11 | Truth of Varying Shades: On Political Fact-Checking and Fake News | 1 |
| 12 | 207 | |
| 13 | Truth of Varying Shades: Analyzing Language in Fake News and Political Fact-Checkingbreakdown → | 490 |
| 14 | 5 | |
| 15 | 9 | |
| 16 | 14 | |
| 17 | 33 | |
| 18 | 91 |
About Jin Yea Jang
Jin Yea Jang is a scholar working on Communication, Artificial Intelligence and Sociology and Political Science, having authored 18 papers that have together received 919 indexed citations. Recurring topics across this work include Misinformation and Its Impacts (7 papers), Speech and dialogue systems (6 papers) and Social Media and Politics (5 papers). The work is most often cited by research in Information Systems (454 citations), Sociology and Political Science (751 citations) and Artificial Intelligence (530 citations). Jin Yea Jang has collaborated with scholars based in United States and South Korea. Frequent co-authors include Svitlana Volkova, Hannah Rashkin, Eunsol Choi, Yejin Choi, Nathan O. Hodas, Kyle Shaffer, Kyungsik Han, Dongwon Lee, Patrick C. Shih and San Kim. Their work appears in journals such as Computer, Empirical Methods in Natural Language Processing and Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing.
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.