Evaluation of the Brazilian Portuguese version of linguistic inquiry and word count 2015 (BP-LIWC2015).
Text psycholinguistic features are a valuable source for various research topics since they are used to obtain psychological, social, and linguistic aspects from written texts using dictionary files. These files are structured in categories, which are defined as groups of dictionary words that tap a...
| Publicado en: | Language Resources & Evaluation Vol. 58; no. 1; pp. 203 - 223 |
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| Autores principales: | , , , , |
| Formato: | Artículo |
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Springer Nature
Mar2024
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| Materias: | |
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=hlh&AN=176079985&site=ehost-live header: @attributes: shortDbName: hlh uiTerm: 176079985 longDbName: Humanities International Complete uiTag: AN controlInfo: bkinfo: jinfo: jid: 1574020X 179V jtl: Language Resources & Evaluation issn: 1574020X maglogo: N pubinfo: dt: Mar2024 vid: 58 iid: 1 pid: 237 pub: Springer Nature artinfo: ui: 176079985 10.1007/s10579-023-09647-2 ppf: 203 ppct: 20 formats: fmt: – @attributes: type: T – @attributes: type: P size: 1.1MB tig: atl: Evaluation of the Brazilian Portuguese version of linguistic inquiry and word count 2015 (BP-LIWC2015). aug: au: Carvalho, Flavio Junior, Fabio Paschoal Ogasawara, Eduardo Ferrari, Lilian Guedes, Gustavo affil: CEFET/RJ, Rio de Janeiro, Brazil UFRJ, Rio de Janeiro, Brazil su: Portuguese language Word frequency Encyclopedias & dictionaries Psycholinguistics Classification algorithms sug: subj: Portuguese language Word frequency Encyclopedias & dictionaries Psycholinguistics Classification algorithms keyword: Brazilian portuguese LIWC LIWC2015 Machine learning. Sentiment analysis Text analysis ab: Text psycholinguistic features are a valuable source for various research topics since they are used to obtain psychological, social, and linguistic aspects from written texts using dictionary files. These files are structured in categories, which are defined as groups of dictionary words that tap a particular domain (e.g., negative emotion words). The Linguistic Inquiry Word Count (LIWC) is a vastly used and versatile computer-based language analysis tool designed for text psycholinguistic analysis. The most recent version of the default English dictionary is LIWC2015, as it was released with the 2015 version of the LIWC software. The literature has recently introduced the latest Brazilian Portuguese LIWC dictionary (BP-LIWC2015), developed with the same categories as the LIWC 2015 English dictionary. However, the literature has also reported the need to evaluate BP-LIWC2015. In this scenario, this work investigates three questions: (i) Since LIWC2015 shows consistent improvements over the English dictionary developed in 2007 (LIWC2007), does BP-LIWC2015 achieves better text classification results than the older Brazilian Portuguese dictionary (BP-LIWC2007)? (ii) What is the equivalence between BP-LIWC2015 and BP-LIWC2007 with LIWC2015? (iii) Are there significant differences between Brazilian Portuguese dictionaries? To answer these questions, we conducted text classification experiments with four datasets and seven classification algorithms to compare the two Brazilian Portuguese LIWC dictionaries reported in the literature (i.e., 2007 and 2015). Second, we used a bilingual Portuguese-English scientific news collection to analyze the correlation between LIWC2015 and Brazilian Portuguese LIWC dictionaries. The results indicate that BP-LIWC2015 outperforms the older version in Brazilian Portuguese text classification. Finally, we found a more significant correlation between BP-LIWC2015 and the original English dictionary than the older version. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: Y custom: Language Resources & Evaluation is a copyright of Springer, 2024. All Rights Reserved. item: Language Resources & Evaluation holder: Springer Nature dt: @attributes: year: 2024 holdings: @attributes: islocal: N |
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