Mohamed Ben Ammar
- Artificial Intelligence top 10%
- Computer Science Applications top 5%
- Experimental and Cognitive Psychology
- Information Systems top 10%
- Computer Vision and Pattern Recognition
- Co-authors
- Adel M. AlimiMahmoud NéjiZied KechaouF. CornélisMonji KherallahMatthias BarralMohamed ElleuchAli Wali
- Topics
- Intelligent Tutoring Systems and Adaptive Learning (7 papers)Social Robot Interaction and HRI (6 papers)Emotion and Mood Recognition (5 papers)
- Partner nations
- TunisiaSaudi ArabiaFrance
In The Last Decade
Mohamed Ben Ammar
49 papers receiving 447 citations
Peers
Comparison fields: 5 of 109
- Artificial Intelligence 186
- Computer Science Applications 79
- Experimental and Cognitive Psychology 66
- Information Systems 54
- Computer Vision and Pattern Recognition 52
Countries citing papers authored by Mohamed Ben Ammar
This map shows the geographic impact of Mohamed Ben Ammar'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 Mohamed Ben Ammar with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mohamed Ben Ammar more than expected).
Fields of papers citing papers by Mohamed Ben Ammar
This network shows the impact of papers produced by Mohamed Ben Ammar. 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 Mohamed Ben Ammar. The network helps show where Mohamed Ben Ammar may publish in the future.
Co-authorship network of co-authors of Mohamed Ben Ammar
This figure shows the co-authorship network connecting the top 25 collaborators of Mohamed Ben Ammar. A scholar is included among the top collaborators of Mohamed Ben Ammar 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 Mohamed Ben Ammar. Mohamed Ben Ammar is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 12 | |
| 2 | 0 | |
| 3 | 1 | |
| 4 | 2 | |
| 5 | 0 | |
| 6 | 1 | |
| 7 | 10 | |
| 8 | 1 | |
| 9 | 2 | |
| 10 | 10 | |
| 11 | 15 | |
| 12 | 10 | |
| 13 | 20 | |
| 14 | 2 | |
| 15 | Novel Hybrid Method for Sentiment Classification of Movie Reviews. | 7 |
| 16 | 19 | |
| 17 | Agent-Based Collaborative Affective e-Learning Framework. | 28 |
| 18 | Affective e-Learning Framework | 2 |
| 19 | E-learning peer to peer using eeca based on the pecs model | 1 |
| 20 | RESPON KEDELAI (Glycine max L. Merr.) TERHADAP Bradyrhizobium japonicum Strain Hup PADA TANAH MASAM | 3 |
About Mohamed Ben Ammar
Mohamed Ben Ammar is a scholar working on Human-Computer Interaction, Artificial Intelligence and Computer Vision and Pattern Recognition, having authored 54 papers that have together received 484 indexed citations. Recurring topics across this work include Intelligent Tutoring Systems and Adaptive Learning (7 papers), Social Robot Interaction and HRI (6 papers) and Emotion and Mood Recognition (5 papers). The work is most often cited by research in Computer Science Applications (79 citations), Artificial Intelligence (186 citations) and Experimental and Cognitive Psychology (66 citations). Mohamed Ben Ammar has collaborated with scholars based in Tunisia, Saudi Arabia and France. Frequent co-authors include Adel M. Alimi, Mahmoud Néji, Zied Kechaou, F. Cornélis, Monji Kherallah, Matthias Barral, Mohamed Elleuch, Ali Wali, Joseph Gligorov and Elimame Elaloui. Their work appears in journals such as Scientific Reports, Expert Systems with Applications and Biomass and Bioenergy.
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.