Bayan Abu Shawar

29 papers receiving 743 citations

Peers

Bayan Abu Shawar
Comparison fields: 5 of 93
  • Artificial Intelligence 567
  • Sociology and Political Science 137
  • Information Systems 129
  • Social Psychology 110
  • Computer Science Applications 86
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Sabine Seufert Switzerland
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Citations per field
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Citations per year

Countries citing papers authored by Bayan Abu Shawar

Since Specialization
Citations

This map shows the geographic impact of Bayan Abu Shawar'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 Bayan Abu Shawar with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Bayan Abu Shawar more than expected).

Fields of papers citing papers by Bayan Abu Shawar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Bayan Abu Shawar. 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 Bayan Abu Shawar. The network helps show where Bayan Abu Shawar may publish in the future.

Co-authorship network of co-authors of Bayan Abu Shawar

This figure shows the co-authorship network connecting the top 25 collaborators of Bayan Abu Shawar. A scholar is included among the top collaborators of Bayan Abu Shawar 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 Bayan Abu Shawar. Bayan Abu Shawar is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 0
2 5
3 1
4 18
5 1
6 33
7 20
8 3
9 39
10
Bayesian-based instance weighting techniques for instance-based learners
0
11 24
12
Chatbots are natural web interface to information portals
4
13
The Relationship Between Knowledge Management and e-Learning.
5
14 5
15
Using WAP Technology in E-learning.
0
16 92
17
Quality Assurance Procedures: New Enhancements to the Learning Management System at AOU.
1
18
Integrating the Learning Management System with other Online Administrative Systems at AOU.
3
19
A Chatbot as a Novel Corpus Visualization Tool
3
20
A corpus-based approach to generalising a chatbot system
11

About Bayan Abu Shawar

Bayan Abu Shawar is a scholar working on Health Informatics, Artificial Intelligence and Human Factors and Ergonomics, having authored 34 papers that have together received 822 indexed citations. Recurring topics across this work include AI in Service Interactions (14 papers), Topic Modeling (8 papers) and Natural Language Processing Techniques (6 papers). The work is most often cited by research in Health Informatics (38 citations), Artificial Intelligence (567 citations) and Computer Science Applications (86 citations). Bayan Abu Shawar has collaborated with scholars based in United Kingdom, United Arab Emirates and Jordan. Frequent co-authors include Eric Atwell, Khalil El Hindi, Mousa Al-Akhras, Abid Mehmood, Oludare Isaac Abiodun, Ahmad K. Al Hwaitat, Moatsum Alawida, Abiodun Esther Omolara, Brenda Louw and Wajdi Zaghouani. Their work appears in journals such as Language Resources and Evaluation, Knowledge and Information Systems and Computational Intelligence and Neuroscience.

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.

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