Shoaib Jameel
- Artificial Intelligence top 5%
- Social Psychology top 10%
- Applied Psychology top 5%
- Information Systems top 10%
- Experimental and Cognitive Psychology
- Co-authors
- Guandong XuHamad ZoganImran RazzakSteven SchockaertWai LamXianzhi WangZied BouraouiJianlong Zhou
- Topics
- Topic Modeling (30 papers)Natural Language Processing Techniques (18 papers)Text and Document Classification Technologies (9 papers)
- Partner nations
- United KingdomHong KongChina
In The Last Decade
Shoaib Jameel
48 papers receiving 496 citations
Peers
Comparison fields: 5 of 75
- Artificial Intelligence 331
- Social Psychology 164
- Applied Psychology 96
- Information Systems 80
- Experimental and Cognitive Psychology 64
Countries citing papers authored by Shoaib Jameel
This map shows the geographic impact of Shoaib Jameel'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 Shoaib Jameel with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shoaib Jameel more than expected).
Fields of papers citing papers by Shoaib Jameel
This network shows the impact of papers produced by Shoaib Jameel. 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 Shoaib Jameel. The network helps show where Shoaib Jameel may publish in the future.
Co-authorship network of co-authors of Shoaib Jameel
This figure shows the co-authorship network connecting the top 25 collaborators of Shoaib Jameel. A scholar is included among the top collaborators of Shoaib Jameel 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 Shoaib Jameel. Shoaib Jameel 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 | 5 | |
| 3 | 0 | |
| 4 | 2 | |
| 5 | 104 | |
| 6 | 11 | |
| 7 | 69 | |
| 8 | 15 | |
| 9 | 4 | |
| 10 | 6 | |
| 11 | 4 | |
| 12 | 2 | |
| 13 | 6 | |
| 14 | Unsupervised learning of distributional relation vectors | 13 |
| 15 | Inductive reasoning in ontologies using conceptual spaces | 8 |
| 16 | D-GloVe: A feasible least squares model for estimating word embedding densities | 6 |
| 17 | 2 | |
| 18 | 22 | |
| 19 | 0 | |
| 20 | $N$-gram Fragment Sequence Based Unsupervised Domain-Specific Document Readability | 1 |
About Shoaib Jameel
Shoaib Jameel is a scholar working on Artificial Intelligence, Computer Science Applications and Information Systems and Management, having authored 53 papers that have together received 515 indexed citations. Recurring topics across this work include Topic Modeling (30 papers), Natural Language Processing Techniques (18 papers) and Text and Document Classification Technologies (9 papers). The work is most often cited by research in Applied Psychology (96 citations), Artificial Intelligence (331 citations) and Social Psychology (164 citations). Shoaib Jameel has collaborated with scholars based in United Kingdom, Hong Kong and China. Frequent co-authors include Guandong Xu, Hamad Zogan, Imran Razzak, Steven Schockaert, Wai Lam, Xianzhi Wang, Zied Bouraoui, Jianlong Zhou, Fang Chen and Shuiqiao Yang. Their work appears in journals such as IEEE Access, Knowledge-Based Systems and Artificial Intelligence Review.
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.