Rotem Dror

862 citations
17 papers · 490 · h-index 10

Impact in

    • Topic Modeling
    • Natural Language Processing Techniques
    • Advanced Text Analysis Techniques
    • Text Readability and Simplification
    • Sentiment Analysis and Opinion Mining
    • Speech and dialogue systems

Papers in

Rotem Dror

15 papers receiving 452 citations

Peers

Rotem Dror
Comparison fields: 5 of 76
  • Artificial Intelligence 403
  • Health Informatics 9
  • Computer Vision and Pattern Recognition 62
  • Information Systems 62
  • General Social Sciences 8
Replace Timo Schick with:
Timo Schick Germany
Mor Geva United States
Alexander R. Fabbri United States
Niklas Muennighoff United States
Max Bartolo United Kingdom
Alham Fikri Aji United Kingdom
Albert Webson United States
Philippe Laban United States
Segev Shlomov Israel
David Uthus United States
Rotem Dror relative to Timo Schick Germany Timo Schick's profile →
Citations per field
00.5×
Timo Schick · 1×
Citations per year

Countries citing papers authored by Rotem Dror

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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 23 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.

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

All Works

17 of 17 papers shown
#Work
1 2018209
2 201962
3 202443
4 201741
5 202137
6 202024
7 202217
8 202217
9 202013
10 202310
11 20237
12 20235
13 20252
14 20242
15 20201
16 20250
17 20250

About Rotem Dror

Rotem Dror is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Information Systems and Management, Management Information Systems and Information Systems, having authored 17 papers that have together received 490 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), Semantic Web and Ontologies (2 papers), Scientific Computing and Data Management (2 papers), Business Process Modeling and Analysis (1 paper) and Digital and Traditional Archives Management (1 paper). The work is most often cited by research in Artificial Intelligence (403 citations), Health Informatics (9 citations), Computer Vision and Pattern Recognition (62 citations), Information Systems (62 citations) and General Social Sciences (8 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, Moran Mizrahi, Dafna Shahaf, Gabriel Stanovsky, Haoyu Wang and Steffen Eger. Their work appears in journals such as Transactions of the Association for Computational Linguistics, Synthesis lectures on human language technologies, Heritage, Lecture notes in business information processing 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.

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