Elamur Research⌕
☰
home / authors / Mohamed Seghir Hadj Ameur

Mohamed Seghir Hadj Ameur

3 papers on this site · 2019–2021

current affiliationNational Higher School of Statistics and Applied Economy, Algiers, Algeria; National School of Artificial Intelligence, Algiers, Algeria

Mohamed Seghir Hadj Ameur has 3 papers on this site, in 2019–2021, most of them on Semitic languages, Sentiment & emotion, Named entity recognition; often with Hassina Aliane.

OpenAlex · ORCID · h-index 8 · 19 works · 261 citations OpenAlex, 2026-10-14

3 works on this site · 7 citations in our library

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

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.

Topics

Semitic languages3Sentiment & emotion2Named entity recognition1Bias, fairness & safety1

Works by year

2020s

20212 papers

2010s

20191 paper

Papers

The most cited first (OpenAlex and our library).

  1. AraCOVID19-MFH: Arabic COVID-19 Multi-label Fake News and Hate Speech Detection Dataset (2021 · 16 citations)
    The paper addresses the lack of rich Arabic resources for detecting COVID-19 misinformation. Most existing fake news corpora use only a binary real/fake label, which cannot handle opinion posts that are neither true nor false, and they ignore how urgently a post needs verification. The authors built AraCOVID19-MFH, a…
  2. ANETAC: Arabic Named Entity Transliteration and Classification Dataset (2019 · 7 citations)
    Research on Arabic named entity transliteration has been held back by a lack of training data. The only freely available English-Arabic resource the authors found has fewer than 13k pairs. This paper releases ANETAC, a dataset of 79,924 English-Arabic named entity pairs. Each pair is labelled as Person, Location, or…
  3. AraCOVID19-SSD: Arabic COVID-19 Sentiment and Sarcasm Detection Dataset (2021 · 4 citations)
    COVID-19 posts on social media often carry sarcasm, and sarcasm makes automatic opinion mining harder because the literal wording hides the writer's real attitude.

Co-authors here

1 co-author with a page, the most papers together first.

Cited by

Papers of our library cite their works 7 times (of the 140 884 papers whose bibliographies we read); 1 citing paper with a page here →.

This page in Markdown → https://md.research.elamur.ai/free/en/authors/mohamed-seghir-hadj-ameur/