Rotem Dror
Impact in
- Artificial Intelligence top 5%
- Topic Modeling
- Natural Language Processing Techniques
- Advanced Text Analysis Techniques
- Text Readability and Simplification
- Speech and dialogue systems
- Sentiment Analysis and Opinion Mining
Papers in
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- Topic Modeling 12
- Natural Language Processing Techniques 11
- Advanced Text Analysis Techniques 3
- Machine Learning and Data Classification 3
- Semantic Web and Ontologies 1
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- Scientific Computing and Data Management 2
- Co-authors
- Roi Reichart (6 shared papers)Segev Shlomov (4 shared papers)Dan Roth (4 shared papers)Daniel Deutsch (4 shared papers)Marina Bogomolov (1 shared paper)Dafna Shahaf (1 shared paper)Gabriel Stanovsky (1 shared paper)Moran Mizrahi (1 shared paper)
- Journals
- Transactions of the Association for Computational Linguistics (3 papers)Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (1 paper)
- Partner nations
- IsraelUnited StatesGermany
In The Last Decade
Rotem Dror
13 papers receiving 389 citations
Peers
Comparison fields: 5 of 72
- Artificial Intelligence 366
- Health Informatics 8
- Computer Vision and Pattern Recognition 57
- General Social Sciences 8
- Information Systems 51
Countries citing papers authored by Rotem Dror
This map shows the geographic impact of Rotem Dror'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 Rotem Dror with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Rotem Dror more than expected).
Fields of papers citing papers by Rotem Dror
This network shows the impact of papers produced by Rotem Dror. 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 Rotem Dror. The network helps show where Rotem Dror may publish in the future.
Co-authors
The 18 scholars most cited alongside Rotem Dror, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2018 | 191 | |
| 2 | 2019 | 56 | |
| 3 | 2017 | 38 | |
| 4 | 2021 | 35 | |
| 5 | 2024 | 29 | |
| 6 | 2020 | 17 | |
| 7 | 2022 | 16 | |
| 8 | 2022 | 14 | |
| 9 | 2023 | 10 | |
| 10 | 2020 | 8 | |
| 11 | 2023 | 6 | |
| 12 | 2023 | 5 | |
| 13 | 2025 | 2 |
About Rotem Dror
Rotem Dror is a scholar working on Artificial Intelligence, Information Systems and Management, Information Systems, Computer Vision and Pattern Recognition and Infectious Diseases, having authored 13 papers that have together received 427 indexed citations. Recurring topics across this work include Topic Modeling (12 papers), Natural Language Processing Techniques (11 papers), Advanced Text Analysis Techniques (3 papers), Machine Learning and Data Classification (3 papers), Scientific Computing and Data Management (2 papers), Semantic Web and Ontologies (1 paper), Software Engineering Research (1 paper) and Multimodal Machine Learning Applications (1 paper). The work is most often cited by research in Artificial Intelligence (366 citations), Health Informatics (8 citations), Computer Vision and Pattern Recognition (57 citations), General Social Sciences (8 citations) and Information Systems (51 citations). Rotem Dror has collaborated with scholars based in Israel, United States and Germany. Frequent co-authors include Roi Reichart, Segev Shlomov, Dan Roth, Daniel Deutsch, Marina Bogomolov, Dafna Shahaf, Gabriel Stanovsky, Moran Mizrahi, Yang Gao and Steffen Eger. Their work appears in journals such as Transactions of the Association for Computational Linguistics and Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies.
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.