Shafiq Joty
- Artificial Intelligence top 0.2%
- Information Systems top 0.5%
- Computer Vision and Pattern Recognition top 2%
- Management Science and Operations Research top 2%
- Sociology and Political Science top 5%
- Co-authors
- Steven C. H. HoiWeishi WangYue WangPengfei LiuHelen MengGiuseppe CareniniRaymond T. NgPreslav Nakov
- Topics
- Topic Modeling (122 papers)Natural Language Processing Techniques (99 papers)Advanced Text Analysis Techniques (29 papers)
- Journals
- Journal of Medical Internet ResearchNeurocomputingIEEE Transactions on Knowledge and Data Engineering
- Partner nations
- SingaporeUnited StatesCanada
In The Last Decade
Shafiq Joty
164 papers receiving 4.2k citations
Hit Papers
Peers
Comparison fields: 5 of 132
- Artificial Intelligence 3.1k
- Information Systems 1.1k
- Computer Vision and Pattern Recognition 667
- Management Science and Operations Research 337
- Sociology and Political Science 301
Countries citing papers authored by Shafiq Joty
This map shows the geographic impact of Shafiq Joty'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 Shafiq Joty with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shafiq Joty more than expected).
Fields of papers citing papers by Shafiq Joty
This network shows the impact of papers produced by Shafiq Joty. 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 Shafiq Joty. The network helps show where Shafiq Joty may publish in the future.
Co-authorship network of co-authors of Shafiq Joty
This figure shows the co-authorship network connecting the top 25 collaborators of Shafiq Joty. A scholar is included among the top collaborators of Shafiq Joty 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 Shafiq Joty. Shafiq Joty 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 | 0 | |
| 3 | 0 | |
| 4 | 0 | |
| 5 | 6 | |
| 6 | 9 | |
| 7 | 6 | |
| 8 | 0 | |
| 9 | 4 | |
| 10 | 14 | |
| 11 | 20 | |
| 12 | 71 | |
| 13 | 5 | |
| 14 | 10 | |
| 15 | 24 | |
| 16 | 1 | |
| 17 | 38 | |
| 18 | 97 | |
| 19 | 166 | |
| 20 | Fine-grained Opinion Mining with Recurrent Neural Networks and Word Embeddingsbreakdown → | 290 |
About Shafiq Joty
Shafiq Joty is a scholar working on Artificial Intelligence, Computational Mathematics and Computer Vision and Pattern Recognition, having authored 180 papers that have together received 4.4k indexed citations. Recurring topics across this work include Topic Modeling (122 papers), Natural Language Processing Techniques (99 papers) and Advanced Text Analysis Techniques (29 papers). The work is most often cited by research in Artificial Intelligence (3.1k citations), Software (294 citations) and Health Informatics (95 citations). Shafiq Joty has collaborated with scholars based in Singapore, United States and Canada. Frequent co-authors include Steven C. H. Hoi, Weishi Wang, Yue Wang, Pengfei Liu, Helen Meng, Giuseppe Carenini, Raymond T. Ng, Preslav Nakov, Lluı́s Màrquez and Mourad Ouzzani. Their work appears in journals such as Journal of Medical Internet Research, Neurocomputing and IEEE Transactions on Knowledge and Data Engineering.
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.