Chaya Liebeskind
Biographic Data
| ID | 6521811 |
|---|---|
| NAME | Chaya Liebeskind |
| GIVEN NAMES | Chaya |
| FAMILY NAME | Liebeskind |
| SIGNATURE | LIEBESKIND C |
| AFFILIATIONS | Jerusalem College of Technology |
| ORCID | 0000-0003-0476-3796 |
| VERIFIED | Yes |
| TOTAL WORKS | 12 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 12 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2023 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 0 |
Improving Hebrew offensive language classification using LLM-assisted human-in-the-loop annotation
This study explores the challenges and opportunities of using large language models (LLMs) for automatic annotation of offensive language in Hebrew. The analysis is based on a six-level taxonomy of offensive discourse – covering offensiveness, target, target presence, vulgarity, offense strength, and specific aspects – enabling systematic examination of nuanced Hebrew patterns. Several prompting strategies were tested, including few-shot, role-ba…
Questions in monologues
The present study analyzes the types of interrogative, such as yes/no questions, wh-questions, or alternative questions, and their semantic and pragmatic functions in a multilingual parallel corpus of spoken monologues extracted from the TED Talks transcripts in five languages: English, European Portuguese, Lithuanian, Bulgarian, and Hebrew. The corpus was developed with English as the pivot language, and the examples are aligned in all five lang…
Sarcastic comments on Reddit and Twitter
he paper deals with automatic detection of sarcasm on social media (Reddit and Twitter). The objective of this paper is to explore various expressions used to encode sarcasm in comments tagged as sarcastic by social media users. The difference between sarcasm and irony and the descriptions of these terms are presented in the theoretical part. The datasets extracted from Reddit and Twitter exceeded 1.2 million comments. The research methods used i…
Multiword Discourse Markers Across Languages
Discourse markers (DMs) are linguistic expressions that convey different semantic and pragmatic values, managing and organizing the structure of spoken and written discourses. They can be either single‐word or multiword expressions (MWE), made up of conjunctions, adverbs, and prepositional phrases. Although DMs are the focus of many studies, some questions regarding the interoperability of taxonomies and automatic identification and classificatio…
Classifying offensive language in Arabic
This paper presents a streamlined taxonomy for categorizing offensive language in Arabic, specifically Modern Standard Arabic (MSA) and the Levantine dialect. Addressing a gap in the existing literature, which has mainly focused on Indo-European languages, our taxonomy divides offensive language into seven levels (six explicit and one implicit). We adapted our framework from the simplified offensive language (SOL) taxonomy by (Lewandowska-Tomaszc…
Opinion events and stance types
The paper tests conversational Large Language Models, instructed to produce stance expression types (affective, relational, epistemic, and moral) and their contexts in Opinion (Speech) Events (Lewandowska-Tomaszczyk, Barbara, Chaya Liebeskind, Anna Baczkowska, Jurate Ruzaite, Ardita Dylgjeri, Ledia Kazazi & Erika Lombart 2023. Opinion events: Types and opinion markers in English social media discourse. Lodz Papers in Pragmatics 19(2). 447–481). I…
Implicit offensive language taxonomy
The aim of this paper is to present a proposal of implicitness typology. The theoretical model we propose is compliant with neo-Gricean pragmatics and is explicitly designed to cover instances of offensive language on social media. The implicitness framework we propound has been empirically verified by means of a corpus-assisted analysis and computational method of word embeddings (Word2Vec and FastText), which, in principle, have supported the s…
Hebrew offensive language taxonomy and dataset
This paper introduces a streamlined taxonomy for categorizing offensive language in Hebrew, addressing a gap in the literature that has, until now, largely focused on Indo-European languages. Our taxonomy divides offensive language into seven levels (six explicit and one implicit level). We based our work on the simplified offensive language (SOL) taxonomy introduced in (Lewandowska-Tomaszczyk et al. 2021a) hoping that our adjustment of SOL to th…
LLOD schema for Simplified Offensive Language Taxonomy in multilingual detection and applications
The goal of the paper is to present a Simplified Offensive Language (SOL) Taxonomy, its application and testing in the Second Annotation Campaign conducted between March-May 2023 on four languages: English, Czech, Lithuanian, and Polish to be verified and located in LLOD. Making reference to the previous Offensive Language taxonomic models proposed mostly by the same COST Action Nexus Linguarum WG 4.1.1 team, the number and variety of the categor…
Opinion Events
The paper investigates various definitions of the concept of opinion as opposed to factual or evidence-based statements and proposes a taxonomy of opinions expressed in English as identified in selected social media. A discussion situates opinions in the realm of pragmatics and reaches to philosophy of language and cognitive science. The research methodology combines a thorough linguistic analysis of opinions, proposing their multifaceted taxonom…
An integrated explicit and implicit offensive language taxonomy
The current study represents an integrated model of explicit and implicit offensive language taxonomy. First, it focuses on a definitional revision and enrichment of the explicit offensive language taxonomy by reviewing the collection of available corpora and comparing tagging schemas applied there. The study relies mainly on the categories originally proposed by Zampieri et al. (2019) in terms of offensive language categorization schemata. After…
Clickbait detection in Hebrew
The prevalence of sensationalized headlines and deceptive narratives in online content has prompted the need for effective clickbait detection methods. This study delves into the nuances of clickbait in Hebrew, scrutinizing diverse features such as linguistic and structural features, and exploring various types of clickbait in Hebrew, a language that has received relatively limited attention in this context. Utilizing a range of machine learning …
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Hebrew offensive language taxonomy and dataset
This paper introduces a streamlined taxonomy for categorizing offensive language in Hebrew, addressing a gap in the literature that has, until now, largely focused on Indo-European languages. Our taxonomy divides offensive language into seven levels (six explicit and one implicit level). We based our work on the simplified offensive language (SOL) taxonomy introduced in (Lewandowska-Tomaszczyk et al. 2021a) hoping that our adjustment of SOL to th…
LLOD schema for Simplified Offensive Language Taxonomy in multilingual detection and applications
The goal of the paper is to present a Simplified Offensive Language (SOL) Taxonomy, its application and testing in the Second Annotation Campaign conducted between March-May 2023 on four languages: English, Czech, Lithuanian, and Polish to be verified and located in LLOD. Making reference to the previous Offensive Language taxonomic models proposed mostly by the same COST Action Nexus Linguarum WG 4.1.1 team, the number and variety of the categor…
Opinion Events
The paper investigates various definitions of the concept of opinion as opposed to factual or evidence-based statements and proposes a taxonomy of opinions expressed in English as identified in selected social media. A discussion situates opinions in the realm of pragmatics and reaches to philosophy of language and cognitive science. The research methodology combines a thorough linguistic analysis of opinions, proposing their multifaceted taxonom…
An integrated explicit and implicit offensive language taxonomy
The current study represents an integrated model of explicit and implicit offensive language taxonomy. First, it focuses on a definitional revision and enrichment of the explicit offensive language taxonomy by reviewing the collection of available corpora and comparing tagging schemas applied there. The study relies mainly on the categories originally proposed by Zampieri et al. (2019) in terms of offensive language categorization schemata. After…
Clickbait detection in Hebrew
The prevalence of sensationalized headlines and deceptive narratives in online content has prompted the need for effective clickbait detection methods. This study delves into the nuances of clickbait in Hebrew, scrutinizing diverse features such as linguistic and structural features, and exploring various types of clickbait in Hebrew, a language that has received relatively limited attention in this context. Utilizing a range of machine learning …
Classifying offensive language in Arabic
This paper presents a streamlined taxonomy for categorizing offensive language in Arabic, specifically Modern Standard Arabic (MSA) and the Levantine dialect. Addressing a gap in the existing literature, which has mainly focused on Indo-European languages, our taxonomy divides offensive language into seven levels (six explicit and one implicit). We adapted our framework from the simplified offensive language (SOL) taxonomy by (Lewandowska-Tomaszc…
Opinion events and stance types
The paper tests conversational Large Language Models, instructed to produce stance expression types (affective, relational, epistemic, and moral) and their contexts in Opinion (Speech) Events (Lewandowska-Tomaszczyk, Barbara, Chaya Liebeskind, Anna Baczkowska, Jurate Ruzaite, Ardita Dylgjeri, Ledia Kazazi & Erika Lombart 2023. Opinion events: Types and opinion markers in English social media discourse. Lodz Papers in Pragmatics 19(2). 447–481). I…
Implicit offensive language taxonomy
The aim of this paper is to present a proposal of implicitness typology. The theoretical model we propose is compliant with neo-Gricean pragmatics and is explicitly designed to cover instances of offensive language on social media. The implicitness framework we propound has been empirically verified by means of a corpus-assisted analysis and computational method of word embeddings (Word2Vec and FastText), which, in principle, have supported the s…
Questions in monologues
The present study analyzes the types of interrogative, such as yes/no questions, wh-questions, or alternative questions, and their semantic and pragmatic functions in a multilingual parallel corpus of spoken monologues extracted from the TED Talks transcripts in five languages: English, European Portuguese, Lithuanian, Bulgarian, and Hebrew. The corpus was developed with English as the pivot language, and the examples are aligned in all five lang…
Sarcastic comments on Reddit and Twitter
he paper deals with automatic detection of sarcasm on social media (Reddit and Twitter). The objective of this paper is to explore various expressions used to encode sarcasm in comments tagged as sarcastic by social media users. The difference between sarcasm and irony and the descriptions of these terms are presented in the theoretical part. The datasets extracted from Reddit and Twitter exceeded 1.2 million comments. The research methods used i…
Multiword Discourse Markers Across Languages
Discourse markers (DMs) are linguistic expressions that convey different semantic and pragmatic values, managing and organizing the structure of spoken and written discourses. They can be either single‐word or multiword expressions (MWE), made up of conjunctions, adverbs, and prepositional phrases. Although DMs are the focus of many studies, some questions regarding the interoperability of taxonomies and automatic identification and classificatio…
Improving Hebrew offensive language classification using LLM-assisted human-in-the-loop annotation
This study explores the challenges and opportunities of using large language models (LLMs) for automatic annotation of offensive language in Hebrew. The analysis is based on a six-level taxonomy of offensive discourse – covering offensiveness, target, target presence, vulgarity, offense strength, and specific aspects – enabling systematic examination of nuanced Hebrew patterns. Several prompting strategies were tested, including few-shot, role-ba…
Computer Science (10 works) · Linguistics (8 works) · Artificial Intelligence (7 works) · Natural language processing (7 works) · Hate Speech and Cyberbullying Detection (6 works) · Offensive (6 works) · Swearing, Euphemism, Multilingualism (6 works) · Psychology (5 works) · Philosophy (4 works) · Annotation (3 works)