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Cross-lingual few-shot hate speech and offensive language detection using meta learning
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In: ISSN: 2169-3536 ; EISSN: 2169-3536 ; IEEE Access ; https://hal.archives-ouvertes.fr/hal-03559484 ; IEEE Access, IEEE, 2022, 10, pp.14880-14896. ⟨10.1109/ACCESS.2022.3147588⟩ (2022)
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FAIRsharing record for: General Ontology for Linguistic Description ... : GOLD ...
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Unsupervised quantification of entity consistency between photos and text in real-world news ...
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Müller-Budack, Eric. - : Hannover : Institutionelles Repositorium der Leibniz Universität Hannover, 2022
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EMBEDDIA tools output example corpus of Estonian, Croatian and Latvian news articles 1.0
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Freienthal, Linda; Pelicon, Andraž; Martinc, Matej; Škrlj, Blaž; Krustok, Ivar; Pranjić, Marko; Cabrera-Diego, Luis Adrián; Purver, Matthew; Pollak, Senja; Kuulmets, Hele-Andra; Shekhar, Ravi; Koloski, Boshko. - : Ekspress Meedia Group, 2022. : Styria Media Group, 2022
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Abstract:
This dataset contains articles from EMBEDDIA Media partners with various information added by the tools developed within the EMBEDDIA project: - 12,390 Estonian articles from 2019 with tags given by Ekspress Meedia. The complete dataset without the output of EMBEDDIA tools is available at http://hdl.handle.net/11356/1408 - 5,000 Croatian articles from autumn of 2010 with tags given by 24sata. The complete dataset without the output of EMBEDDIA tools is available at http://hdl.handle.net/11356/1410 - 15,264 Latvian articles from 2019 with tags given by Ekspress Meedia. The complete dataset without the output of EMBEDDIA tools is available at http://hdl.handle.net/11356/1409 All the articles in the dataset have been analysed with texta-mlp Python package (https://pypi.org/project/texta-mlp/) via the EMBEDDIA Media assistant's Texta Toolkit (https://docs.texta.ee/). The tools used to analyse the articles were the following: - Latin1 and Latin2 Name Entity Recognition Tool modules (Cabrera-Diego et al., 2021, both described in https://aclanthology.org/2021.bsnlp-1.12/) . The Latin 1 results can be found folders annotated_articles_ner_latin1/ and annotated_articles_all_tools/, while the Latin 2 results are in annotated_articles_nerlatin2/ or annotated_articles_all_tools/. - RAKUN keyword extractor. RAKUN (Škrlj et al. 2019) is an unsupervised system for keyword extraction, so it can be used for any language. It detects keywords by turning text into a graph and the most important nodes in the graph mostly turn out to be the keywords. It is described in https://link.springer.com/chapter/10.1007/978-3-030-31372-2_26. The keyword annotation results can be found in the folder annotated_articles_rakun/ or annotated_articles_all_tools/. - TNT-KID keyword extractor. TNT-KID (Martinc et al. 2021, ) is a supervised system for automatic keyword extraction. It was trained on a corpus of articles with human-assigned keywords. For Croatian, the annotators were 24sata editors, for Estonian the Ekspress Meedia staff and for Latvian the Latvian Delfi staff. The system is further documented at https://doi.org/10.1017/S1351324921000127. For Croatian only TNT-KID was applied, while for Estonian and Latvian, the TNT-KID with TF-IDF, and extension by Koloski et al. (https://aclanthology.org/2021.hackashop-1.4.pdf) was used. The results of applying this tool are found in the folder annotated articles tnt_kid/ or annotated articles all tools/. - Sentiment analysis. Our news sentiment analyser (Pelicon et al. 2020) labels a news article as being of positive, negative, or neutral sentiment, using a fine-tuned multilingual BERT model, which was trained on Slovene sentiment annotated news articles. The system is further documented in https://doi.org/10.3390/app10175993. The results of this tools are found in the folder annotated articles sentiment/ or annotated articles all tools/. All the data is encoded in "JSON Lines" format. Each folder has its own README file which explains the structure of the files.
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Keyword:
keyword extraction; named entity recognition; sentiment classification
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URL: http://hdl.handle.net/11356/1485
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О ЛЕКСИКО-ГРАММАТИЧЕСКИХ РАЗРЯДАХ ИМЕН СУЩЕСТВИТЕЛЬНЫХ В ТАБАСАРАНСКОМ ЯЗЫКЕ ... : ABOUT LEXICAL AND GRAMMATICAL CATEGORIES OF NOUNS IN THE TABASARAN LANGUAGE ...
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Mining an English-Chinese parallel Dataset of Financial News
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In: Journal of Open Humanities Data; Vol 8 (2022); 9 ; 2059-481X (2022)
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Discriminating Bacterial Infection from Other Causes of Fever Using Body Temperature Entropy Analysis
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In: Entropy; Volume 24; Issue 4; Pages: 510 (2022)
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The Multilingual Pragmatics of New Englishes: An Analysis of Question Tags in Nigerian English
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The phonetics and phonology of Hong Kong English: a study of fricatives
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Code: Drift in a Popular Metal Oxide Sensor Dataset Reveals Limitations for Gas Classification Benchmarks ...
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Code: Drift in a Popular Metal Oxide Sensor Dataset Reveals Limitations for Gas Classification Benchmarks ...
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Addressing multilingualism in the GoTriple discovery platform ...
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Addressing multilingualism in the GoTriple discovery platform ...
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The Terms of “You(s)”: How the Term of Address Used by Conversational Agents Influences User Evaluations in French and German Linguaculture ...
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'Muscles of mussels' and 'hooks of bananas' - the (incipient) numeral classifier system of Ugare (Tivoid, Cameroon/Nigeria) ...
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Towards reconstructing a Proto-Tivoid numeral classifier system ...
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Measuring Semantic Similarity of Documents by Using Named Entity Recognition Methods
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In: Masters (2022)
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