Sunipa Dev

3.0k citations
23 papers · 425 · h-index 9

Impact in

Papers in

Journals
ACM Transactions on Interactive Intelligent Systems (1 paper)Studies in computational intelligence (1 paper)Proceedings of the AAAI Conference on Artificial Intelligence (1 paper)Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (1 paper)Edinburgh Research Explorer (University of Edinburgh) (1 paper)

In The Last Decade

Sunipa Dev

19 papers receiving 407 citations

Peers

Sunipa Dev
Comparison fields: 5 of 58
  • Health Informatics 30
  • Safety Research 91
  • General Social Sciences 29
  • Artificial Intelligence 274
  • Computer Science Applications 17
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Citations per field
00.5×2×2.7×
Kellie Webster · 1×
Citations per year

Countries citing papers authored by Sunipa Dev

Since Specialization
Citations

This map shows the geographic impact of Sunipa Dev'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 Sunipa Dev with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sunipa Dev more than expected).

Fields of papers citing papers by Sunipa Dev

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Sunipa Dev. 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 Sunipa Dev. The network helps show where Sunipa Dev may publish in the future.

Co-authors

The 25 scholars most cited alongside Sunipa Dev, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Sunipa Dev Line = papers co-authored together Sunipa Dev links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 23 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2023105
2 202192
3 202082
4 202235
5 202125
6 202213
7 202413
8 202212
9 20239
10 20236
11 20236
12 20206
13 20235
14 20235
15 20234
16 20212
17 20242
18 20242
19 20221
20 20160

About Sunipa Dev

Sunipa Dev is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Health Informatics, Speech and Hearing and Information Systems, having authored 23 papers that have together received 425 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (9 papers), Topic Modeling (8 papers), Hate Speech and Cyberbullying Detection (5 papers), Text Readability and Simplification (4 papers), Software Engineering Research (2 papers), Psychology of Moral and Emotional Judgment (1 paper), Multi-Agent Systems and Negotiation (1 paper) and Innovative Teaching Methodologies in Social Sciences (1 paper). The work is most often cited by research in Health Informatics (30 citations), Safety Research (91 citations), General Social Sciences (29 citations), Artificial Intelligence (274 citations) and Computer Science Applications (17 citations). Sunipa Dev has collaborated with scholars based in United States, United Kingdom and India. Frequent co-authors include Jeff M. Phillips, Vivek Srikumar, Kai-Wei Chang, Tao Li, Emily Denton, Anaelia Ovalle, Alex S. Taylor, Robin N. Brewer, Arjun Subramonian and Shaun K. Kane. Their work appears in journals such as ACM Transactions on Interactive Intelligent Systems, Studies in computational intelligence, Proceedings of the AAAI Conference on Artificial Intelligence, Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies and Edinburgh Research Explorer (University of Edinburgh).

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.

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