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Zoher Orabe

Zoher Orabe has 2 papers in our library, in 2020, most of them on Sentiment & emotion, Semitic languages; often with Anas Al-Abood, Bushr Haddad, Nada Ghneim.

2 papers in our library · 2020

OpenAlex · ORCID · h-index 3 · 8 works · 34 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 7 times in our library · ⭐ Paper Stars ranking: #8366

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

🎓University of TurkuTurku · Finland2025–2026 · 4 paperscurrent

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine.

 Fields, topics and concepts

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

📚 Shelves 6The field of science this work belongs to (OpenAlex fields).Artificial Intelligence · 2 worksComputer Science · 2 worksCommunication · 1 workSocial Sciences · 1 workArts and Humanities · 1 workLanguage and Linguistics · 1 work

🧭 Topics 2Research subjects and languages the work is about.Semitic languages · 2 worksSentiment & emotion · 2 works

 Works by year

2020s

20202 papers

 Papers

The most cited first (OpenAlex and our library).

  1. Arabic Offensive Language Detection with Attention-based Deep Neural Networks (2020 · 27 citations)
    This paper is a system description for the OSACT4 shared task on Arabic tweets. The task has two binary subtasks: spotting offensive language (subtask A) and spotting hate speech (subtask B). The 10,000-tweet dataset is heavily skewed. About 19% of tweets are offensive and only 5% are hateful, and every hateful tweet…
  2. DoTheMath at SemEval-2020 Task 12 : Deep Neural Networks with Self Attention for Arabic Offensive Language Detection (2020 · 6 citations)
    The paper describes the DoTheMath team's entry for the Arabic track (Sub-Task A) of OffensEval at SemEval-2020. The task is to label Arabic tweets as offensive (OFF) or not (NOT OFF). The training data is heavily skewed, with only about one tweet in five offensive.

 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 7 times (of the 149,439 papers whose bibliographies we read); 5 citing papers with a page here →.

Updated

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