Sweta Agrawal
- Artificial Intelligence top 10%
- Computer Vision and Pattern Recognition
- Information Systems
- Computer Networks and Communications
- Sociology and Political Science
- Co-authors
- Marine CarpuatWeijia XuLuke ZettlemoyerMichael LewisChunting ZhouMarjan GhazvininejadMarianna J. MartindaleJoel Tetreault
- Topics
- Natural Language Processing Techniques (17 papers)Topic Modeling (13 papers)Text Readability and Simplification (9 papers)
- Journals
- Transactions of the Association for Computational LinguisticsORCA Online Research @Cardiff (Cardiff University)UvA-DARE (University of Amsterdam)
- Partner nations
- United StatesUnited KingdomPortugal
In The Last Decade
Sweta Agrawal
16 papers receiving 137 citations
Peers
Comparison fields: 5 of 45
- Artificial Intelligence 121
- Computer Vision and Pattern Recognition 27
- Information Systems 10
- Computer Networks and Communications 6
- Sociology and Political Science 5
Countries citing papers authored by Sweta Agrawal
This map shows the geographic impact of Sweta Agrawal'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 Sweta Agrawal with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sweta Agrawal more than expected).
Fields of papers citing papers by Sweta Agrawal
This network shows the impact of papers produced by Sweta Agrawal. 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 Sweta Agrawal. The network helps show where Sweta Agrawal may publish in the future.
Co-authorship network of co-authors of Sweta Agrawal
This figure shows the co-authorship network connecting the top 25 collaborators of Sweta Agrawal. A scholar is included among the top collaborators of Sweta Agrawal 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 Sweta Agrawal. Sweta Agrawal is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 0 | |
| 3 | 0 | |
| 4 | 1 | |
| 5 | 0 | |
| 6 | 0 | |
| 7 | 0 | |
| 8 | 1 | |
| 9 | 1 | |
| 10 | 24 | |
| 11 | 0 | |
| 12 | 3 | |
| 13 | 5 | |
| 14 | 26 | |
| 15 | 6 | |
| 16 | 14 | |
| 17 | 17 | |
| 18 | 28 | |
| 19 | 11 | |
| 20 | 7 |
About Sweta Agrawal
Sweta Agrawal is a scholar working on Artificial Intelligence, Computer Science Applications and Transportation, having authored 23 papers that have together received 148 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (17 papers), Topic Modeling (13 papers) and Text Readability and Simplification (9 papers). The work is most often cited by research in Artificial Intelligence (121 citations), Computer Vision and Pattern Recognition (27 citations) and Health Informatics (1 citation). Sweta Agrawal has collaborated with scholars based in United States, United Kingdom and Portugal. Frequent co-authors include Marine Carpuat, Weijia Xu, Luke Zettlemoyer, Michael Lewis, Chunting Zhou, Marjan Ghazvininejad, Weijia Xu, Marianna J. Martindale, Joel Tetreault and Ankur Garg. Their work appears in journals such as Transactions of the Association for Computational Linguistics, ORCA Online Research @Cardiff (Cardiff University) and UvA-DARE (University of Amsterdam).
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.