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Eshrag Refaee

Eshrag Refaee has 5 papers in our library, in 2014–2022, most of them on Semitic languages, Sentiment & emotion, Morphology; often with Verena Rieser, Basem Ahmed, Motaz Saad.

5 papers in our library · 2014–2022

OpenAlex · ORCID · h-index 12 · 22 works · 500 citations OpenAlex, 2026-10-14

📄 5 works in our library · 🔗 Cited 48 times in our library · ⭐ Paper Stars ranking: #5187

The profile is the library's match of the name; two people with one name are not always told apart.

Elsewhere: Google Scholar · Semantic Scholar · dblp · ACL Anthology

 Affiliations

🎓Jazan UniversityGazan · Saudi Arabia2017–2026 · 16 papersEmployment · Vice Dean, Computer Sciences and Information Technologycurrent🎓Heriot-Watt UniversityEdinburgh · United Kingdom2014–2017 · 6 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 1 more institution on single bylines are not listed.

 Fields, topics and concepts

Of its works in our library, with the number of works on each.

📚 Shelves 8The field of science this work belongs to (OpenAlex fields).Artificial Intelligence · 5 worksComputer Science · 5 worksExperimental and Cognitive Psychology · 3 worksPsychology · 3 worksArts and Humanities · 3 worksLanguage and Linguistics · 3 worksSocial Sciences · 1 workSociology and Political Science · 1 work

🧭 Topics 4Research subjects and languages the work is about.Semitic languages · 5 worksSentiment & emotion · 4 worksMorphology · 1 workEvaluation & benchmarks · 1 work

 Works by year

2020s

20221 paper

2010s

20161 paper20151 paper20142 papers

 Papers

The most cited first (OpenAlex and our library).

  1. An Arabic Twitter Corpus for Subjectivity and Sentiment Analysis (2014 · 172 citations)
    Sentiment work on Arabic lags far behind English. Part of the reason is the language's rich morphology. Another part is that annotated social-media data was rarely shared. Refaee and Rieser address this gap by building a hand-annotated collection of Arabic tweets for analysing subjectivity and sentiment (SSA).
  2. iLab-Edinburgh at SemEval-2016 Task 7: A Hybrid Approach for Determining Sentiment Intensity of Arabic Twitter Phrases (2016 · 32 citations)
    The paper describes the system that won the Arabic Twitter subtask of SemEval-2016 Task 7. The task gives a word or short phrase from Arabic tweets and asks for a real-valued sentiment intensity (SI) score between 0 and 1. Scores below 0.5 mean negative and scores above mean positive. Earlier Arabic work mostly…
  3. Benchmarking Machine Translated Sentiment Analysis for Arabic Tweets (2015 · 31 citations)
    The paper asks whether Arabic tweets can be classified for sentiment without building a dedicated Arabic system.
  4. Evaluating Distant Supervision for Subjectivity and Sentiment Analysis on Arabic Twitter Feeds (2014 · 27 citations)
    The paper asks whether noisy automatic labels can replace small hand-labelled sets for subjectivity and sentiment analysis (SSA) of Arabic tweets. The motivation is that classifiers trained on limited manual data break down when topics shift over time. The authors collected tweets across a year:
  5. AraBEM at WANLP 2022 Shared Task: Propaganda Detection in Arabic Tweets (2022 · 4 citations)
    This paper describes team AraBEM's entry to the WANLP 2022 shared task on detecting propaganda in Arabic tweets.

 Co-authors here

3 co-authors with a page, the most papers together first.

Venues

Where their works here were published, the most works first, with the editions of those that have a page.

 Cited by

Papers of our library cite their works 48 times (of the 149,439 papers whose bibliographies we read); 38 citing papers with a page here →.

Updated

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