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ZENODO
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ZENODO
Dataset . 2020
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Data sources: Datacite
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Zipf's laws of meaning in Catalan Datasets

Authors: , Català; , Baixeries; , Ferrer-I-Cancho; , Padró; , Hernández-Fernández;

Zipf's laws of meaning in Catalan Datasets

Abstract

This are the datasets referenced in the paper "Zipf’s laws of meaning in Catalan". The datasets are: DIEC2_CTILC_senseCG. It contains the following information: lema: lemma in Catalan n_sentits: number of meanings for that lemma, freq: frequency for that lemma. rank of that lemma. Those lemmas are contained in both of the following corpuses: CTILC: https://ctilc.iec.cat. DIEC: Institut d’Estudis Catalans. Diccionari de la llengua catalana [en línia]. 2a ed. Barcelona: Edicions 62: Enciclopèdia Catalana, 2007. [1a ed., 1995] <https://dlc.iec.cat/> [Consulta: October 2020] DIEC2_GLISSANDO_senseCG. It contains the following information: lema: lemma in Catalan n_sentits: number of meanings for that lemma, freq: frequency for that lemma. rank of that lemma. Those lemmas are contained in both of the following corpuses: Glissando: http://catalog.elra.info/en-us/repository/browse/ELRA-S0407/ DIEC: Institut d’Estudis Catalans. Diccionari de la llengua catalana [en línia]. 2a ed. Barcelona: Edicions 62: Enciclopèdia Catalana, 2007. [1a ed., 1995] <https://dlc.iec.cat/> [Consulta: October 2020]

This work has been funded by the project PRO2020-S03 (RCO03080449Ling ̈u ́ıstica Quantitativa, Institut d'Estudis Catalans). JB, RFC and AHF450are also funded by the grant TIN2017-89244-R from Ministerio de Econo-451mia, Industria y Competitividad (Gobierno de Espa ̃na) and the recognition4522017SGR-856 (MACDA) from AGAUR (Generalitat de Catalunya).

{"references": ["Institut d'Estudis Catalans. Diccionari de la llengua catalana [en l\u00ednia]. 2a ed. Barcelona: Edicions 62: Enciclop\u00e8dia Catalana, 2007. [1a ed., 1995] [Consulta: October 2020]"]}

Keywords

Law of meaning distribution, Meaning-frequency law, Zipf'slaw, Catalan, DIEC2, CTILC corpus, Glissando Corpus

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This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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