Princess Sumaya University for Technology

31.8k citations
2.4k papers ·

Impact in

Papers in

Princess Sumaya University for Technology

2.0k papers receiving 29.7k citations

Peers

Princess Sumaya University for Technology
Comparison fields: 5 of 234
  • Modeling and Simulation 3.0k
  • Information Systems and Management 2.1k
  • Artificial Intelligence 8.0k
  • Information Systems 5.2k
  • Signal Processing 2.4k
Replace Zarqa University with:
Zarqa University Jordan
Al-Zaytoonah University of Jordan Jordan
Amman Arab University Jordan
Al-Ahliyya Amman University Jordan
Middle East University Jordan
Arab Academy for Science, Technology, and Maritime Transport Egypt
Jadara University Jordan
German University in Cairo Egypt
Birzeit University Palestinian Territory
Nile University Egypt
Princess Sumaya University for Technology relative to Zarqa University Jordan Zarqa University's profile →
Citations per field
00.5×2×2.7×
Zarqa University · 1×
Citations per year

Countries citing scholars working at Princess Sumaya University for Technology

Since Specialization
Citations

This map shows the geographic impact of research produced by authors working at Princess Sumaya University for Technology. 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 papers produced at Princess Sumaya University for Technology with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Princess Sumaya University for Technology more than expected).

Fields of papers published by authors at Princess Sumaya University for Technology

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers affiliated with Princess Sumaya University for Technology at the time of their publication. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers affiliated with Princess Sumaya University for Technology at the time of their publication.

About Princess Sumaya University for Technology

In recent decades, authors affiliated with Princess Sumaya University for Technology have published 2.4k papers, which have received a total of 31.8k indexed citations . Scholars at this organization have produced 148 papers in Information Systems and Management, 227 papers in Signal Processing, 678 papers in Artificial Intelligence, 451 papers in Information Systems and 407 papers in Computer Networks and Communications on the topics of Network Security and Intrusion Detection (181 papers), Advanced Malware Detection Techniques (158 papers), Organizational and Employee Performance (138 papers), Technology Adoption and User Behaviour (135 papers), Digital Marketing and Social Media (81 papers), Spam and Phishing Detection (79 papers), Blockchain Technology Applications and Security (78 papers) and IoT and Edge/Fog Computing (77 papers). Their work is cited by papers focused on Modeling and Simulation (3.0k citations), Information Systems and Management (2.1k citations), Artificial Intelligence (8.0k citations), Information Systems (5.2k citations) and Signal Processing (2.4k citations). Authors at Princess Sumaya University for Technology collaborate with scholars in Jordan, United States and Saudi Arabia and have published in prestigious journals including IEEE Access, Multimedia Tools and Applications, Sustainability, Neural Computing and Applications and Electronics. Some of Princess Sumaya University for Technology's most productive authors include Mohammad Sababheh, Roshdi Rashid Khalil, Abdelrahman Yousef, Mohammed Al Horani, Qasem S. Abu Al-Haija, Arafat Awajan, Mahmoud Mohammad Migdadi, Ahmad Hiasat, Ali Al‐Haj and Moh’d Anwer AL-Shboul.

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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