Muhammad Abulaish

2.1k citations
131 papers · 1.6k · h-index 20

Impact in

Papers in

    • Spam and Phishing Detection 32
    • Web Data Mining and Analysis 15
    • Advanced Text Analysis Techniques 28
    • Semantic Web and Ontologies 24
    • Sentiment Analysis and Opinion Mining 20
    • Topic Modeling 17

Muhammad Abulaish

119 papers receiving 1.5k citations

Peers

Muhammad Abulaish
Comparison fields: 5 of 94
  • Information Systems 888
  • Artificial Intelligence 972
  • Signal Processing 301
  • Statistical and Nonlinear Physics 276
  • Computer Networks and Communications 407
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Citations per year

Countries citing papers authored by Muhammad Abulaish

Since Specialization
Citations

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

Fields of papers citing papers by Muhammad Abulaish

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Muhammad Abulaish. 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 Muhammad Abulaish. The network helps show where Muhammad Abulaish may publish in the future.

Co-authors

The 24 scholars most cited alongside Muhammad Abulaish, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Muhammad Abulaish Line = papers co-authored together Muhammad Abulaish links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 131 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2013157
2 2018108
3 201374
4 201270
5 200960
6 202158
7 201949
8 201549
9 202049
10 201449
11 202144
12 201837
13 200634
14 200728
15 201427
16 201427
17 200625
18 201023
19 201321
20 201321

About Muhammad Abulaish

Muhammad Abulaish is a scholar working on Information Systems, Artificial Intelligence, Statistical and Nonlinear Physics, Signal Processing and Computer Networks and Communications, having authored 131 papers that have together received 1.6k indexed citations. Recurring topics across this work include Complex Network Analysis Techniques (35 papers), Spam and Phishing Detection (32 papers), Advanced Text Analysis Techniques (28 papers), Semantic Web and Ontologies (24 papers), Sentiment Analysis and Opinion Mining (20 papers), Topic Modeling (17 papers), Network Security and Intrusion Detection (17 papers) and Web Data Mining and Analysis (15 papers). The work is most often cited by research in Information Systems (888 citations), Artificial Intelligence (972 citations), Signal Processing (301 citations), Statistical and Nonlinear Physics (276 citations) and Computer Networks and Communications (407 citations). Muhammad Abulaish has collaborated with scholars based in India, Saudi Arabia and Australia. Frequent co-authors include Faraz Ahmed, Mohd Fazil, Lipika Dey, Ashraf Kamal, Tarique Anwar, Mohammed Javeed Zaki, Tanvir Ahmad, M. N. Doja, Majed Alrubaian and Nur Al Hasan Haldar. Their work appears in journals such as IEEE Access, Journal of Intelligent & Fuzzy Systems, Digital Investigation, IEEE Transactions on Information Forensics and Security and Expert Systems with Applications.

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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