Junyi Jessy Li
- Artificial Intelligence top 5%
- Information Systems top 5%
- Software top 5%
- Computer Vision and Pattern Recognition
- Computer Science Applications top 10%
- Co-authors
- Ani NenkovaMilos GligoricGreg DurrettJiyang ZhangDaniel Preoțiuc-PietroMarine CarpuatByron WallaceWei-Jen Ko
- Topics
- Topic Modeling (32 papers)Natural Language Processing Techniques (28 papers)Text Readability and Simplification (17 papers)
- Partner nations
- United StatesNetherlandsIndia
In The Last Decade
Junyi Jessy Li
46 papers receiving 525 citations
Peers
Comparison fields: 5 of 54
- Artificial Intelligence 421
- Information Systems 135
- Software 70
- Computer Vision and Pattern Recognition 33
- Computer Science Applications 32
Countries citing papers authored by Junyi Jessy Li
This map shows the geographic impact of Junyi Jessy Li'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 Junyi Jessy Li with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Junyi Jessy Li more than expected).
Fields of papers citing papers by Junyi Jessy Li
This network shows the impact of papers produced by Junyi Jessy Li. 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 Junyi Jessy Li. The network helps show where Junyi Jessy Li may publish in the future.
Co-authorship network of co-authors of Junyi Jessy Li
This figure shows the co-authorship network connecting the top 25 collaborators of Junyi Jessy Li. A scholar is included among the top collaborators of Junyi Jessy Li 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 Junyi Jessy Li. Junyi Jessy Li 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 | 1 | |
| 3 | 1 | |
| 4 | 1 | |
| 5 | 3 | |
| 6 | 0 | |
| 7 | 21 | |
| 8 | 5 | |
| 9 | 2 | |
| 10 | 15 | |
| 11 | 3 | |
| 12 | 6 | |
| 13 | An Annotated Dataset of Discourse Modes in Hindi Stories | 3 |
| 14 | 14 | |
| 15 | Natural Language Processing and Program Analysis for Supporting Todo Comments as Software Evolves. | 8 |
| 16 | Expressively vulgar: The socio-dynamics of vulgarity and its effects on sentiment analysis in social media. | 21 |
| 17 | Improving the Annotation of Sentence Specificity | 9 |
| 18 | 11 | |
| 19 | Cross-lingual Discourse Relation Analysis: A corpus study and a semi-supervised classification system | 12 |
| 20 | 1 |
About Junyi Jessy Li
Junyi Jessy Li is a scholar working on Software, Artificial Intelligence and General Social Sciences, having authored 49 papers that have together received 550 indexed citations. Recurring topics across this work include Topic Modeling (32 papers), Natural Language Processing Techniques (28 papers) and Text Readability and Simplification (17 papers). The work is most often cited by research in Software (70 citations), Health Informatics (19 citations) and Artificial Intelligence (421 citations). Junyi Jessy Li has collaborated with scholars based in United States, Netherlands and India. Frequent co-authors include Ani Nenkova, Milos Gligoric, Greg Durrett, Jiyang Zhang, Daniel Preoțiuc-Pietro, Marine Carpuat, Byron Wallace, Wei-Jen Ko, Kapil Thadani and Raymond J. Mooney. Their work appears in journals such as The Journals of Gerontology Series B, Language Resources and Evaluation and NPARC.
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.