Dhafar Hamed
- Artificial Intelligence top 10%
- Information Systems
- Health Information Management top 5%
- Computer Vision and Pattern Recognition
- Sociology and Political Science
- Co-authors
- Jwan K. AlwanAyad R. AbbasMohamed Nazih OmriAhmed T. SadiqAbir HussainDhiya Al‐JumeilyWasiq KhanPanos Liatsis
- Topics
- Sentiment Analysis and Opinion Mining (10 papers)Advanced Text Analysis Techniques (7 papers)Text and Document Classification Technologies (3 papers)
- Journals
- SHILAP Revista de lepidopterologíaIEEE AccessNeural Computing and Applications
- Partner nations
- IraqUnited KingdomUnited Arab Emirates
In The Last Decade
Dhafar Hamed
24 papers receiving 223 citations
Peers
Comparison fields: 5 of 82
- Artificial Intelligence 117
- Information Systems 39
- Health Information Management 30
- Computer Vision and Pattern Recognition 27
- Sociology and Political Science 25
Countries citing papers authored by Dhafar Hamed
This map shows the geographic impact of Dhafar Hamed'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 Dhafar Hamed with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dhafar Hamed more than expected).
Fields of papers citing papers by Dhafar Hamed
This network shows the impact of papers produced by Dhafar Hamed. 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 Dhafar Hamed. The network helps show where Dhafar Hamed may publish in the future.
Co-authorship network of co-authors of Dhafar Hamed
This figure shows the co-authorship network connecting the top 25 collaborators of Dhafar Hamed. A scholar is included among the top collaborators of Dhafar Hamed based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Dhafar Hamed. Dhafar Hamed is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 1 | |
| 3 | 0 | |
| 4 | 1 | |
| 5 | 1 | |
| 6 | 0 | |
| 7 | 0 | |
| 8 | 2 | |
| 9 | 0 | |
| 10 | 17 | |
| 11 | 3 | |
| 12 | 2 | |
| 13 | 1 | |
| 14 | 1 | |
| 15 | 18 | |
| 16 | 47 | |
| 17 | 15 | |
| 18 | 17 | |
| 19 | 9 | |
| 20 | 2 |
About Dhafar Hamed
Dhafar Hamed is a scholar working on Health Informatics, Health Information Management and Artificial Intelligence, having authored 30 papers that have together received 233 indexed citations. Recurring topics across this work include Sentiment Analysis and Opinion Mining (10 papers), Advanced Text Analysis Techniques (7 papers) and Text and Document Classification Technologies (3 papers). The work is most often cited by research in Health Information Management (30 citations), Artificial Intelligence (117 citations) and Information Systems (39 citations). Dhafar Hamed has collaborated with scholars based in Iraq, United Kingdom and United Arab Emirates. Frequent co-authors include Jwan K. Alwan, Ayad R. Abbas, Mohamed Nazih Omri, Ahmed T. Sadiq, Abir Hussain, Dhiya Al‐Jumeily, Wasiq Khan, Panos Liatsis, Russell Keenan and Paul Fergus. Their work appears in journals such as SHILAP Revista de lepidopterología, IEEE Access and Neural Computing and Applications.
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.