Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
SemEval-2020 Task 12: Multilingual Offensive Language Identification in Social Media (OffensEval 2020)
2020244 citationsPreslav Nakov, Hamdy Mubarak et al.profile →
Farasa: A Fast and Furious Segmenter for Arabic
2016239 citationsAhmed Abdelalí, Kareem Darwish et al.profile →
Abusive Language Detection on Arabic Social Media
2017205 citationsHamdy Mubarak, Kareem Darwish et al.Edinburgh Research Explorer (University of Edinburgh)profile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
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This map shows the geographic impact of Hamdy Mubarak'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 Hamdy Mubarak with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hamdy Mubarak more than expected).
This network shows the impact of papers produced by Hamdy Mubarak. 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 Hamdy Mubarak. The network helps show where Hamdy Mubarak may publish in the future.
Co-authorship network of co-authors of Hamdy Mubarak
This figure shows the co-authorship network connecting the top 25 collaborators of Hamdy Mubarak.
A scholar is included among the top collaborators of Hamdy Mubarak 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 Hamdy Mubarak. Hamdy Mubarak is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Chowdhury, Shammur Absar, Hamdy Mubarak, Ahmed Abdelalí, et al.. (2020). A Multi-Platform Arabic News Comment Dataset for Offensive Language Detection. Language Resources and Evaluation. 6203–6212.25 indexed citations
Mubarak, Hamdy. (2018). Build fast and accurate lemmatization for Arabic. Language Resources and Evaluation. 1128–1132.6 indexed citations
13.
Magdy, Walid, et al.. (2018). Part-of-Speech Tagging for Arabic Gulf Dialect Using Bi-LSTM. Language Resources and Evaluation. 3925–3932.11 indexed citations
14.
Nakov, Preslav, Doris Hoogeveen, Lluı́s Màrquez, et al.. (2017). SemEval-2017 Task 3: Community Question Answering. Institutional Research Information System (Università degli Studi di Trento). 27–48.121 indexed citations
15.
Mubarak, Hamdy, Kareem Darwish, & Walid Magdy. (2017). Abusive Language Detection on Arabic Social Media. Edinburgh Research Explorer (University of Edinburgh). 52–56.205 indexed citations breakdown →
16.
Mubarak, Hamdy & Ahmed Abdelalí. (2016). Arabic to English Person Name Transliteration using Twitter.. Language Resources and Evaluation. 351–355.5 indexed citations
Ali, Ahmed, Hamdy Mubarak, & Stephan Vogel. (2014). Advances in dialectal Arabic speech recognition: a study using Twitter to improve Egyptian ASR.. IWSLT.19 indexed citations
19.
Darwish, Kareem, Ahmed Abdelalí, & Hamdy Mubarak. (2014). Using Stem-Templates to Improve Arabic POS and Gender/Number Tagging. Language Resources and Evaluation. 2926–2931.23 indexed citations
20.
Mubarak, Hamdy, et al.. (2013). A review of Siddha cardiology and cardioprotective herbs.. International Journal of Herbal Medicine. 1(4). 71–75.3 indexed citations
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.