2019
DOI: 10.35869/vial.v0i16.93
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An n-gram based approach to the automatic classification of schoolchildren’s writing

Abstract: This article focuses on the analysis of schoolchildren’s writing (throughout the whole primary school period) using sets of morphological labels (n-grams). We analyzed the sets of bigrams and trigrams from a group of literary texts written by Catalan schoolchildren in order to identify which bigrams and trigrams can help discriminate between texts from the three cycles into which the Spanish primary education system is divided: lower cycle (6- and 7-year-olds), middle cycle (8- and 9-year- olds) and upper cycl… Show more

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Cited by 2 publications
(12 citation statements)
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“…In this way, we compared more homogeneous texts, and on average the percentage of correct classifications was higher than 70% in both the original classifications and the cross-validation (Table 19). This percentage of correct classifications is similar to the one found to group together texts according to the age of their authors (Cicres & Queralt, 2019).…”
Section: Discussionsupporting
confidence: 85%
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“…In this way, we compared more homogeneous texts, and on average the percentage of correct classifications was higher than 70% in both the original classifications and the cross-validation (Table 19). This percentage of correct classifications is similar to the one found to group together texts according to the age of their authors (Cicres & Queralt, 2019).…”
Section: Discussionsupporting
confidence: 85%
“…In this study, we explored the efficiency of using n-grams (specifically bigrams and trigrams) of morphological categories to determine the sex of children between the ages of seven and 12 who wrote a version of the story Little Red Riding Hood in Catalan. In previous studies, n-grams of morphological categories have proven useful in characterizing the age of children (Cicres & Queralt, 2019), as well as for determining the authors of the written texts (in this case, texts written by adults) within the context of forensic linguistics (Diederich et al, 2000;Kulmizev et al, 2017).…”
Section: Discussionmentioning
confidence: 99%
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