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# Natalia Vanetik

5 paper cards in Mova's library · 2022–2026

Natalia Vanetik wrote 5 of the papers Mova reads, in 2022–2026; often with [Chaya Liebeskind](https://md.mova.elamur.ai/free/en/docs/papers/authors/chaya-liebeskind/), [Marina Litvak](https://md.mova.elamur.ai/free/en/docs/papers/authors/marina-litvak/), Gili Berger Hefetz.

[OpenAlex](https://openalex.org/A5080435987) · [ORCID](https://orcid.org/0000-0002-4939-1415) · [**h-index 11**](https://openalex.org/authors/A5080435987) · [633 citations](https://openalex.org/authors/A5080435987) · [104 works](https://openalex.org/works?filter=author.id:A5080435987) — openalex, 2026-10-18

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

Elsewhere: [Google Scholar](https://scholar.google.com/citations?view_op=search_authors&mauthors=Natalia+Vanetik) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Natalia+Vanetik) · [dblp](https://dblp.org/search?q=Natalia+Vanetik) · [ACL Anthology](https://aclanthology.org/search/?q=Natalia+Vanetik) · [ORCID](https://orcid.org/orcid-search/search?searchQuery=Natalia+Vanetik)

## Papers

1. **[Annotation Matters: Resolving Cross-Corpus Performance Drops in Hebrew Offensive Language Detection](https://md.mova.elamur.ai/free/en/docs/papers/aclbulk-2026-hefetz-annotation-matters-resolving-cross-corpus/)** *(2026)* Hebrew offensive-language detectors trained on one forum corpus lose much of their accuracy on two external corpora, a Facebook set and a Twitter set.
2. **[Towards Safer Hebrew Communication: A Dataset for Offensive Language Detoxification](https://md.mova.elamur.ai/free/en/docs/papers/aclbulk-2025-vanetik-safer-hebrew-communication-dataset-offensive/)** *(2025)* The paper builds HeDetox, 600 Hebrew sentence pairs in which an explicitly offensive forum comment is paired with a non-offensive rewrite.
3. **[From Linguistics to Practice: a Case Study of Offensive Language Taxonomy in Hebrew](https://md.mova.elamur.ai/free/en/docs/papers/aclbulk-2024-liebeskind-linguistics-practice-case-study-offensive/)** *(2024)* The paper applies a Hebrew translation of the explicit-offence taxonomy of Lewandowska-Tomaszczyk et al. (2023) to Hebrew social-media text. Candidate offensive terms were found by co-occurrence (Dice coefficient) from 67 seed terms, and 683 were chosen by hand. Tweets were then extracted with those terms, and 450…
4. **[Detection of Negative Campaign in Israeli Municipal Elections](https://md.mova.elamur.ai/free/en/docs/papers/aclbulk-2022-litvak-detection-negative-campaign-israeli-municipal/)** *(2022)* The paper introduces TONIC, a dataset of Hebrew Facebook posts by 27 mayoral candidates in 12 Israeli cities (2018 municipal elections).
5. **[Offensive language detection in Hebrew: can other languages help?](https://md.mova.elamur.ai/free/en/docs/papers/lingbulk-2022-litvak-offensive-language-detection-hebrew-can/)** *(2022)* The authors build a binary offensive-language classifier for Hebrew, using a new set of 5217 annotated Facebook comments (two labels per comment, Kappa 0.82), and compare it with Arabic (9000 tweets) and English (OLID, 13 240 tweets).

## Co-authors (9)

- [Chaya Liebeskind](https://md.mova.elamur.ai/free/en/docs/papers/authors/chaya-liebeskind/) ×4
- [Marina Litvak](https://md.mova.elamur.ai/free/en/docs/papers/authors/marina-litvak/) ×4
- Gili Berger Hefetz
- Lior Liberov
- Omar Hmdia
- Or Machlouf
- Rizek Abu Madeghem
- Sagiv Talker
- Yossef Haim Shrem
- [← previous Natalia Silveira](https://md.mova.elamur.ai/free/en/docs/papers/authors/natalia-silveira/)
- [next → Nathan Gilbert](https://md.mova.elamur.ai/free/en/docs/papers/authors/nathan-gilbert/)
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