Ibrahim Abu Farha
- Artificial Intelligence top 2%
- Topic Modeling 9
- Sentiment Analysis and Opinion Mining 7
- Natural Language Processing Techniques 7
- Advanced Text Analysis Techniques 6
- Text and Document Classification Technologies 1
- Hate Speech and Cyberbullying Detection 1
- Information Systems top 10%
- Journals
- Information Processing & Management (1 paper)Journal of King Saud University - Computer and Information Sciences (1 paper)Edinburgh Research Explorer (University of Edinburgh) (5 papers)
- Partner nations
- United KingdomUnited StatesPalestinian Territory
In The Last Decade
Ibrahim Abu Farha
11 papers receiving 444 citations
Peers
Comparison fields: 5 of 42
- Artificial Intelligence 480
- Information Systems 77
- Communication 18
- Human-Computer Interaction 11
- Signal Processing 13
Countries citing papers authored by Ibrahim Abu Farha
This map shows the geographic impact of Ibrahim Abu Farha'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 Ibrahim Abu Farha with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ibrahim Abu Farha more than expected).
Fields of papers citing papers by Ibrahim Abu Farha
This network shows the impact of papers produced by Ibrahim Abu Farha. 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 Ibrahim Abu Farha. The network helps show where Ibrahim Abu Farha may publish in the future.
Co-authorship network
The 5 scholars most cited alongside Ibrahim Abu Farha, 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 | 2024 | 1 | |
| 2 | 2022 | 8 | |
| 3 | 2022 | 68 | |
| 4 | 2022 | 6 | |
| 5 | Benchmarking Transformer-based Language Models for Arabic Sentiment and Sarcasm Detection | 2021 | 41 |
| 6 | Overview of the WANLP 2021 Shared Task on Sarcasm and Sentiment Detection in Arabic | 2021 | 50 |
| 7 | From Arabic Sentiment Analysis to Sarcasm Detection: The ArSarcasm Dataset | 2020 | 68 |
| 8 | Multitask Learning for Arabic Offensive Language and Hate-Speech Detection | 2020 | 28 |
| 9 | 2020 | 79 | |
| 10 | 2019 | 56 | |
| 11 | 2019 | 106 |
About Ibrahim Abu Farha
Ibrahim Abu Farha is a scholar working on Artificial Intelligence, Infectious Diseases and Organic Chemistry, having authored 11 papers that have together received 511 indexed citations. Recurring topics across this work include Topic Modeling (9 papers), Sentiment Analysis and Opinion Mining (7 papers), Natural Language Processing Techniques (7 papers), Advanced Text Analysis Techniques (6 papers), Text and Document Classification Technologies (1 paper) and Hate Speech and Cyberbullying Detection (1 paper). The work is most often cited by research in Artificial Intelligence (480 citations), Information Systems (77 citations) and Communication (18 citations). Ibrahim Abu Farha has collaborated with scholars based in United Kingdom, United States and Palestinian Territory. Frequent co-authors include Walid Magdy, Silviu Oprea, Steven Lloyd Wilson, Wajdi Zaghouani and Aziz Qaroush. Their work appears in journals such as Information Processing & Management, Journal of King Saud University - Computer and Information Sciences 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.