Rasha Obeidat

485 total citations
18 papers, 309 citations indexed

About

Rasha Obeidat is a scholar working on Artificial Intelligence, Information Systems and Sociology and Political Science. According to data from OpenAlex, Rasha Obeidat has authored 18 papers receiving a total of 309 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Artificial Intelligence, 4 papers in Information Systems and 3 papers in Sociology and Political Science. Recurrent topics in Rasha Obeidat's work include Topic Modeling (7 papers), Natural Language Processing Techniques (6 papers) and Spam and Phishing Detection (4 papers). Rasha Obeidat is often cited by papers focused on Topic Modeling (7 papers), Natural Language Processing Techniques (6 papers) and Spam and Phishing Detection (4 papers). Rasha Obeidat collaborates with scholars based in Jordan, United States and United Arab Emirates. Rasha Obeidat's co-authors include Anne A. Gharaibeh, Salman D. Al‐Kofahi, Abdulrazzaq Shaamala, Xiaoli Z. Fern, Prasad Tadepalli, Malak Abdullah, Mohammad Al-Ramahi, Yahya Tashtoush, Omar Darwish and Ismail Hmeidi and has published in prestigious journals such as SHILAP Revista de lepidopterología, Heliyon and Language Resources and Evaluation.

In The Last Decade

Rasha Obeidat

16 papers receiving 301 citations

Peers

Rasha Obeidat
Comparison fields: 5 of 74
  • Global and Planetary Change 153
  • Artificial Intelligence 80
  • Ecology 64
  • Atmospheric Science 46
  • Information Systems 35
Replace Zeeshan Shirazi with:
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Zeeshan Shirazi China View profile →
Citations per field, relative to Rasha Obeidat
Rasha Obeidat · 1×
Citations per year, relative to Rasha Obeidat
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Countries citing papers authored by Rasha Obeidat

Since Specialization
Citations

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

Fields of papers citing papers by Rasha Obeidat

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Rasha Obeidat

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

All Works

18 of 18 papers shown
# Work Indexed citations
1 2
2 1
3 0
4 10
5 3
6 10
7 0
8 6
9 1
10 3
11 4
12 191
13 20
14
Joint Neural Entity Disambiguation with Output Space Search
1
15
Label Embedding Approach for Transfer Learning.
2
16
Improving KNN Arabic Text Classification with N-Grams Based Document Indexing
30
17 22
18 3

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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