Ariel Gera
Impact in
- Artificial Intelligence top 10%
- Topic Modeling
- Natural Language Processing Techniques
- Machine Learning and Algorithms
- Sentiment Analysis and Opinion Mining
- Text and Document Classification Technologies
- Advanced Text Analysis Techniques
- Machine Learning and Data Classification
-
- Software Engineering Research
Papers in
-
- Natural Language Processing Techniques 9
- Topic Modeling 9
- Advanced Text Analysis Techniques 4
- Sentiment Analysis and Opinion Mining 2
- Machine Learning and Algorithms 1
- Text and Document Classification Technologies 1
-
- Web Applications and Data Management 1
- Co-authors
- Noam Slonim (10 shared papers)Alon Halfon (6 shared papers)Liat Ein‐Dor (6 shared papers)Eyal Shnarch (8 shared papers)Lena Dankin (5 shared papers)Ranit Aharonov (4 shared papers)Leshem Choshen (6 shared papers)Yoav Katz (2 shared papers)
- Journals
- Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) (1 paper)
- Partner nations
- IsraelUnited States
In The Last Decade
Ariel Gera
8 papers receiving 146 citations
Peers
Comparison fields: 5 of 49
- Artificial Intelligence 128
- Information Systems 27
- Management Science and Operations Research 9
- Management Information Systems 6
- General Social Sciences 2
Countries citing papers authored by Ariel Gera
This map shows the geographic impact of Ariel Gera'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 Ariel Gera with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ariel Gera more than expected).
Fields of papers citing papers by Ariel Gera
This network shows the impact of papers produced by Ariel Gera. 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 Ariel Gera. The network helps show where Ariel Gera may publish in the future.
Co-authors
The 25 scholars most cited alongside Ariel Gera, 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 | 2020 | 79 | |
| 2 | 2022 | 27 | |
| 3 | 2019 | 13 | |
| 4 | 2019 | 12 | |
| 5 | 2019 | 9 | |
| 6 | 2022 | 6 | |
| 7 | 2022 | 5 | |
| 8 | 2024 | 4 | |
| 9 | Cluster & Tune: Enhance BERT Performance in Low Resource Text Classification | 2021 | 1 |
| 10 | 2024 | 0 | |
| 11 | 2023 | 0 | |
| 12 | 2023 | 0 |
About Ariel Gera
Ariel Gera is a scholar working on Artificial Intelligence, Information Systems, Language and Linguistics, Infectious Diseases and Organic Chemistry, having authored 12 papers that have together received 156 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (9 papers), Topic Modeling (9 papers), Advanced Text Analysis Techniques (4 papers), Sentiment Analysis and Opinion Mining (2 papers), Language, Linguistics, Cultural Analysis (1 paper), Web Applications and Data Management (1 paper), Machine Learning and Algorithms (1 paper) and Text and Document Classification Technologies (1 paper). The work is most often cited by research in Artificial Intelligence (128 citations), Information Systems (27 citations), Management Science and Operations Research (9 citations), Management Information Systems (6 citations) and General Social Sciences (2 citations). Ariel Gera has collaborated with scholars based in Israel and United States. Frequent co-authors include Noam Slonim, Alon Halfon, Liat Ein‐Dor, Eyal Shnarch, Lena Dankin, Ranit Aharonov, Leshem Choshen, Yoav Katz, Marina Danilevsky and Yonatan Bilu. Their work appears in journals such as Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers).
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.