Efficiency of national and international software in detection of similarity and plagiarism in manuscripts
Autor(a) principal: | |
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Data de Publicação: | 2022 |
Tipo de documento: | Artigo |
Idioma: | por |
Título da fonte: | Em Questão (Online) |
Texto Completo: | https://seer.ufrgs.br/index.php/EmQuestao/article/view/123123 |
Resumo: | This study aims to identify the efficiency level of fourteen software for detecting similarities between a text with fragments extracted from online content on financial education, found on open access websites, proceedings of academic events and open and restricted access scientific journals. Fragments extracted from the sources were used to create a cohesive text, written in Portuguese, containing literal textual reproductions, paraphrases, translation from the English language and manipulation with insertion of hidden characters and replacement of words by synonyms. The similarity reports generated by the programs were analyzed according to four criteria: 1 identification of correctly cited fragments; 2 identification of plagiarized fragments; 3 identification of texts manipulated to deceive the software; 4 identification of original sources, which were scored on a scale of 0 to 4 points. Although the Turnitin, Strikeplagiarism and Plagscan software obtained the best performance indices, it was found that the programs operate with variable and limited efficiency, which reinforces the conviction that, although they are useful tools for the identification of plagiarism, they contribute significantly limited by aspects such as recognition mainly of literal textual reproductions that do not always correspond to the original source. The original sources of rewritten, manipulated and translated texts were not found by any software. The study contributes to the improvement of the user's ability to choose, use and analyze the similarity reports generated by software, whose efficiency can be greater in the case of using more than one program. |
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Efficiency of national and international software in detection of similarity and plagiarism in manuscriptsEficiencia del software nacional e internacional en la detección de similitud y plagio en manuscritosEficiência de softwares nacionais e internacionais na detecção de similaridade e de plágio em manuscritoplagiarismsimilarity and plagiarismplagiarism detectionanti-plagiarism softwareplagiosimilitud y plagiodetección de plagiosoftware antiplagioplágiosimilaridade e plágiodetecção de plágiosoftware antiplágioThis study aims to identify the efficiency level of fourteen software for detecting similarities between a text with fragments extracted from online content on financial education, found on open access websites, proceedings of academic events and open and restricted access scientific journals. Fragments extracted from the sources were used to create a cohesive text, written in Portuguese, containing literal textual reproductions, paraphrases, translation from the English language and manipulation with insertion of hidden characters and replacement of words by synonyms. The similarity reports generated by the programs were analyzed according to four criteria: 1 identification of correctly cited fragments; 2 identification of plagiarized fragments; 3 identification of texts manipulated to deceive the software; 4 identification of original sources, which were scored on a scale of 0 to 4 points. Although the Turnitin, Strikeplagiarism and Plagscan software obtained the best performance indices, it was found that the programs operate with variable and limited efficiency, which reinforces the conviction that, although they are useful tools for the identification of plagiarism, they contribute significantly limited by aspects such as recognition mainly of literal textual reproductions that do not always correspond to the original source. The original sources of rewritten, manipulated and translated texts were not found by any software. The study contributes to the improvement of the user's ability to choose, use and analyze the similarity reports generated by software, whose efficiency can be greater in the case of using more than one program.Este estudio tiene como objetivo identificar el nivel de eficiencia de catorce software para detectar similitudes entre un texto con fragmentos extraídos de contenido en línea sobre educación financiera, encontrados en sitios web de acceso abierto, anales de eventos académicos y revistas científicas de acceso abierto y restringido. Se utilizaron fragmentos extraídos de las fuentes para crear un texto cohesivo, escrito en portugués, que contenía reproducciones textuales literales, paráfrasis, traducción del idioma inglés y manipulación con inserción de caracteres ocultos y reemplazo de palabras por sinónimos. Los informes de similitud generados por los programas se analizaron según cuatro criterios: 1 identificación de fragmentos correctamente citados; 2 identificación de fragmentos plagiados; 3 identificación de textos manipulados para engañar al software; 4 Identificación de fuentes originales, las cuales se puntuaron en una escala de 0 a 4 puntos. Si bien los software Turnitin, Strikeplagiarism y Plagscan obtuvieron los mejores índices de desempeño, se encontró que los programas operan con eficiencia variable y limitada, lo que refuerza la convicción de que, si bien son herramientas útiles para la identificación del plagio, contribuyen significativamente limitadas por aspectos como el reconocimiento principalmente de reproducciones textuales literales que no siempre corresponden a la fuente original. Ningún software encontró las fuentes originales de los textos reescritos, manipulados y traducidos. El estudio contribuye a la mejora de la capacidad del usuario para elegir, utilizar y analizar los informes de similitud generados por el software, cuya eficiencia puede ser mayor en el caso de utilizar más de un programa.Este estudo visa identificar a eficiência de quatorze softwares de detecção de similaridades em um texto com fragmentos sobre educação financeira, encontrados em websites da internet, anais de eventos acadêmicos e revistas científicas de acesso aberto e restrito. Os fragmentos foram usados para elaborar um texto coeso, escrito em língua portuguesa, contendo reproduções textuais literais, paráfrases, com trechos traduzidos do idioma inglês, manipulados com inserção de caractere oculto e com substituição de palavras por sinônimos. Os relatórios de similaridade gerados pelos softwares foram analisados de acordo com quatro critérios: 1 identificação de fragmentos citados corretamente; 2 identificação de fragmentos plagiados; 3 identificação de textos manipulados para enganar o software; 4 identificação de fontes originais; os quais foram pontuados em uma escala de 0 a 4 pontos. Os softwares Turnitin, StrikePlagiarism, PlagScan e Plagium tiveram performance elevada e CopySpider e Plagium (complemento do Google) foram os mais ineficientes. Constatou-se que os softwares operam com eficiência variável, o que reforça a convicção de que embora sejam ferramentas úteis para a identificação de plágio, contribuem de forma limitada para aspectos como reconhecimento de reproduções textuais literais que nem sempre correspondem à fonte original. As fontes originais de textos reescritos, manipulados e traduzidos não foram encontradas por nenhum software. O estudo contribui para o aprimoramento da capacidade do usuário na escolha, uso e análise dos relatórios de similaridades gerados por softwares, cuja eficiência pode ser maior no caso da utilização de mais de um software.Universidade Federal do Rio Grande do Sul, Faculdade de Biblioteconomia e Comunicação, Programa de Pós-Graduação em Ciência da Informação (Porto Alegre/RS)2022-09-27info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionText;Texto;Avaliado por ParesTextoapplication/pdfhttps://seer.ufrgs.br/index.php/EmQuestao/article/view/12312310.19132/1808-5245284.123123Em Questão; v.28, n.4, out./dez. 2022; 123123Em Questão; v.28, n.4, out./dez. 2022; 123123Em Questão; v.28, n.4, out./dez. 2022; 1231231808-52451807-8893reponame:Em Questão (Online)instname:Universidade Federal do Rio Grande do Sul (UFRGS)instacron:UFRGSporhttps://seer.ufrgs.br/index.php/EmQuestao/article/view/123123/85885Copyright (c) 2022 Marcelo Krokosczhttps://creativecommons.org/licenses/by/4.0info:eu-repo/semantics/openAccessKrokoscz, Marcelo2023-04-17T15:05:31Zoai:seer.ufrgs.br:article/123123Revistahttps://seer.ufrgs.br/emquestao/PUBhttps://seer.ufrgs.br/EmQuestao/oaiemquestao@ufrgs.br||emquestao@ufrgs.br1808-52451807-8893opendoar:2023-04-17T15:05:31Em Questão (Online) - Universidade Federal do Rio Grande do Sul (UFRGS)false |
dc.title.none.fl_str_mv |
Efficiency of national and international software in detection of similarity and plagiarism in manuscripts Eficiencia del software nacional e internacional en la detección de similitud y plagio en manuscritos Eficiência de softwares nacionais e internacionais na detecção de similaridade e de plágio em manuscrito |
title |
Efficiency of national and international software in detection of similarity and plagiarism in manuscripts |
spellingShingle |
Efficiency of national and international software in detection of similarity and plagiarism in manuscripts Krokoscz, Marcelo plagiarism similarity and plagiarism plagiarism detection anti-plagiarism software plagio similitud y plagio detección de plagio software antiplagio plágio similaridade e plágio detecção de plágio software antiplágio |
title_short |
Efficiency of national and international software in detection of similarity and plagiarism in manuscripts |
title_full |
Efficiency of national and international software in detection of similarity and plagiarism in manuscripts |
title_fullStr |
Efficiency of national and international software in detection of similarity and plagiarism in manuscripts |
title_full_unstemmed |
Efficiency of national and international software in detection of similarity and plagiarism in manuscripts |
title_sort |
Efficiency of national and international software in detection of similarity and plagiarism in manuscripts |
author |
Krokoscz, Marcelo |
author_facet |
Krokoscz, Marcelo |
author_role |
author |
dc.contributor.author.fl_str_mv |
Krokoscz, Marcelo |
dc.subject.por.fl_str_mv |
plagiarism similarity and plagiarism plagiarism detection anti-plagiarism software plagio similitud y plagio detección de plagio software antiplagio plágio similaridade e plágio detecção de plágio software antiplágio |
topic |
plagiarism similarity and plagiarism plagiarism detection anti-plagiarism software plagio similitud y plagio detección de plagio software antiplagio plágio similaridade e plágio detecção de plágio software antiplágio |
description |
This study aims to identify the efficiency level of fourteen software for detecting similarities between a text with fragments extracted from online content on financial education, found on open access websites, proceedings of academic events and open and restricted access scientific journals. Fragments extracted from the sources were used to create a cohesive text, written in Portuguese, containing literal textual reproductions, paraphrases, translation from the English language and manipulation with insertion of hidden characters and replacement of words by synonyms. The similarity reports generated by the programs were analyzed according to four criteria: 1 identification of correctly cited fragments; 2 identification of plagiarized fragments; 3 identification of texts manipulated to deceive the software; 4 identification of original sources, which were scored on a scale of 0 to 4 points. Although the Turnitin, Strikeplagiarism and Plagscan software obtained the best performance indices, it was found that the programs operate with variable and limited efficiency, which reinforces the conviction that, although they are useful tools for the identification of plagiarism, they contribute significantly limited by aspects such as recognition mainly of literal textual reproductions that do not always correspond to the original source. The original sources of rewritten, manipulated and translated texts were not found by any software. The study contributes to the improvement of the user's ability to choose, use and analyze the similarity reports generated by software, whose efficiency can be greater in the case of using more than one program. |
publishDate |
2022 |
dc.date.none.fl_str_mv |
2022-09-27 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Text; Texto; Avaliado por Pares Texto |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://seer.ufrgs.br/index.php/EmQuestao/article/view/123123 10.19132/1808-5245284.123123 |
url |
https://seer.ufrgs.br/index.php/EmQuestao/article/view/123123 |
identifier_str_mv |
10.19132/1808-5245284.123123 |
dc.language.iso.fl_str_mv |
por |
language |
por |
dc.relation.none.fl_str_mv |
https://seer.ufrgs.br/index.php/EmQuestao/article/view/123123/85885 |
dc.rights.driver.fl_str_mv |
Copyright (c) 2022 Marcelo Krokoscz https://creativecommons.org/licenses/by/4.0 info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
Copyright (c) 2022 Marcelo Krokoscz https://creativecommons.org/licenses/by/4.0 |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Universidade Federal do Rio Grande do Sul, Faculdade de Biblioteconomia e Comunicação, Programa de Pós-Graduação em Ciência da Informação (Porto Alegre/RS) |
publisher.none.fl_str_mv |
Universidade Federal do Rio Grande do Sul, Faculdade de Biblioteconomia e Comunicação, Programa de Pós-Graduação em Ciência da Informação (Porto Alegre/RS) |
dc.source.none.fl_str_mv |
Em Questão; v.28, n.4, out./dez. 2022; 123123 Em Questão; v.28, n.4, out./dez. 2022; 123123 Em Questão; v.28, n.4, out./dez. 2022; 123123 1808-5245 1807-8893 reponame:Em Questão (Online) instname:Universidade Federal do Rio Grande do Sul (UFRGS) instacron:UFRGS |
instname_str |
Universidade Federal do Rio Grande do Sul (UFRGS) |
instacron_str |
UFRGS |
institution |
UFRGS |
reponame_str |
Em Questão (Online) |
collection |
Em Questão (Online) |
repository.name.fl_str_mv |
Em Questão (Online) - Universidade Federal do Rio Grande do Sul (UFRGS) |
repository.mail.fl_str_mv |
emquestao@ufrgs.br||emquestao@ufrgs.br |
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1789438636720128000 |