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Kathrein Abu Kwaik

Kathrein Abu Kwaik has 5 papers in our library, in 2018–2022, most of them on Semitic languages, Sentiment & emotion; often with Simon Dobnik, Stergios Chatzikyriakidis, Motaz Saad.

5 papers in our library · 2018–2022

OpenAlex · h-index 6 · 10 works · 217 citations OpenAlex, 2026-10-14

📄 5 works in our library · 🔗 Cited 62 times in our library · ⭐ Paper Stars ranking: #6032

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 GothenburgGothenburg · Sweden2018–2020 · 5 papers

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 4The field of science this work belongs to (OpenAlex fields).Artificial Intelligence · 5 worksComputer Science · 5 worksArts and Humanities · 3 worksLanguage and Linguistics · 3 works

🧭 Topics 2Research subjects and languages the work is about.Semitic languages · 5 worksSentiment & emotion · 2 works

 Works by year

2020s

20221 paper20201 paper

2010s

20192 papers20181 paper

 Papers

The most cited first (OpenAlex and our library).

  1. Shami: A Corpus of Levantine Arabic Dialects (2018 · 95 citations)
    Arabic NLP tools are built mostly for Modern Standard Arabic (MSA), but everyday online writing uses regional dialects that differ from MSA in vocabulary and usage.
  2. An Arabic Tweets Sentiment Analysis Dataset (ATSAD) using Distant Supervision and Self Training (2020 · 38 citations)
    Arabic sentiment analysis lacks social-media resources that are both large and reliably labelled. Existing corpora are often small, limited to one dialect, unbalanced, or labelled in ways that distort the original text. The authors build ATSAD, a Twitter corpus of 36K Arabic tweets marked as positive or negative.…
  3. ArbDialectID at MADAR Shared Task 1: Language Modelling and Ensemble Learning for Fine Grained Arabic Dialect Identification (2019 · 22 citations)
    The paper addresses Arabic Dialect Identification at the city level. Telling 26 varieties apart (25 Arab cities plus MSA) is difficult because neighbouring dialects have no fixed spelling and often look nearly identical in writing. The authors built ArbDialectID for Task 1 of the MADAR shared task, using the…
  4. Can Modern Standard Arabic Approaches be used for Arabic Dialects? Sentiment Analysis as a Case Study (2019 · 6 citations)
    The paper asks whether sentiment classifiers built for Modern Standard Arabic (MSA) still work on dialectal Arabic (DA), or whether each dialect needs its own models.
  5. Pre-trained Models or Feature Engineering: The Case of Dialectal Arabic (2022 · 2 citations)
    Published work on Arabic dialects reports results on corpora that differ in size, dialect coverage and quality, so it is hard to say whether neural models really beat classic classifiers on Dialectal Arabic.

 Co-authors here

4 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 62 times (of the 149,439 papers whose bibliographies we read); 46 citing papers with a page here →.

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