Hapax remains: Regularity of low-frequency words in authorial texts

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989592%3A15210%2F21%3A73611800" target="_blank" >RIV/61989592:15210/21:73611800 - isvavai.cz</a>

Výsledek na webu

<a href="https://academic.oup.com/dsh/advance-article/doi/10.1093/llc/fqab077/6413835" target="_blank" >https://academic.oup.com/dsh/advance-article/doi/10.1093/llc/fqab077/6413835</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1093/llc/fqab077" target="_blank" >10.1093/llc/fqab077</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Hapax remains: Regularity of low-frequency words in authorial texts

Popis výsledku v původním jazyce

This article highlights the usual overlook in the literature of regular occurrences of low-frequency words (hapax legomena) in specific authors’ texts. This overlook arises from a linguistic assumption of non-systematic and context-dependent low-frequency word occurrences in extensive texts, and from the tendency of SVM methods to mark low-frequency words as irrelevant compared to the more frequent lexicon (e.g. Boukhaled, M. A. and Ganascia, J.-G. (2015). Using function words for authorship attribution: bag-of-words vs. sequential rules. In The 11th International Workshop on Natural Language Processing and Cognitive Science, October 2014, Venice, Italy. de Gruyter, Natural Language Processing and Cognitive Science Proceedings 2014, pp. 115–122.). Many approaches to authorship attribution are based on the n most frequent ‘function words’, which (1) are grammatically essential, frequent, and therefore included in each text; (2) are not affected by the topic of the text; and (3) reflect the unintentional linguistic activity of the author (Binongo, J. N. G. (2003). Who wrote the 15th book of Oz? An application of multivariate analysis to authorship attribution. Chance, 16(2): 9–17). Hapax legomena meet these conditions as well, except frequency (Baayen, H., van Halteren, H., and Tweedie, F. (1996). Outside the cave of shadows: using syntactic annotation to enhance authorship attribution. Literary and Linguistic Computing, 11(3): 121–32). We test the hypothesis that hapax legomena may work for purposes of authorship attribution based on selecting only hapaxes from whole texts (or randomly selected tokens of hapaxes) while using a specific pre-processed input (eigendecomposition of a cosine distance matrix) to the SVM classifier. This method evaluated the attribution of texts from fourteen Czech authors (yielding ninety-one pairs in total) and Evert, S., Proisl, T., Jannidis, F. et al. (2017). Understanding and explaining Delta measures for authorship attribution. Digital Scholarship in the Humanities, 32(2): 4–16 data set, and proved itself a suitable tool for identifying authors of previously unknown texts. Our method identifies a sparse network of regular occurrences of low-frequency words in different authors’ texts.

Název v anglickém jazyce

Hapax remains: Regularity of low-frequency words in authorial texts

Popis výsledku anglicky

This article highlights the usual overlook in the literature of regular occurrences of low-frequency words (hapax legomena) in specific authors’ texts. This overlook arises from a linguistic assumption of non-systematic and context-dependent low-frequency word occurrences in extensive texts, and from the tendency of SVM methods to mark low-frequency words as irrelevant compared to the more frequent lexicon (e.g. Boukhaled, M. A. and Ganascia, J.-G. (2015). Using function words for authorship attribution: bag-of-words vs. sequential rules. In The 11th International Workshop on Natural Language Processing and Cognitive Science, October 2014, Venice, Italy. de Gruyter, Natural Language Processing and Cognitive Science Proceedings 2014, pp. 115–122.). Many approaches to authorship attribution are based on the n most frequent ‘function words’, which (1) are grammatically essential, frequent, and therefore included in each text; (2) are not affected by the topic of the text; and (3) reflect the unintentional linguistic activity of the author (Binongo, J. N. G. (2003). Who wrote the 15th book of Oz? An application of multivariate analysis to authorship attribution. Chance, 16(2): 9–17). Hapax legomena meet these conditions as well, except frequency (Baayen, H., van Halteren, H., and Tweedie, F. (1996). Outside the cave of shadows: using syntactic annotation to enhance authorship attribution. Literary and Linguistic Computing, 11(3): 121–32). We test the hypothesis that hapax legomena may work for purposes of authorship attribution based on selecting only hapaxes from whole texts (or randomly selected tokens of hapaxes) while using a specific pre-processed input (eigendecomposition of a cosine distance matrix) to the SVM classifier. This method evaluated the attribution of texts from fourteen Czech authors (yielding ninety-one pairs in total) and Evert, S., Proisl, T., Jannidis, F. et al. (2017). Understanding and explaining Delta measures for authorship attribution. Digital Scholarship in the Humanities, 32(2): 4–16 data set, and proved itself a suitable tool for identifying authors of previously unknown texts. Our method identifies a sparse network of regular occurrences of low-frequency words in different authors’ texts.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

60203 - Linguistics

Projekt

—

Návaznosti

O - Projekt operacniho programu

Rok uplatnění

2021

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Digital Scholarship in the Humanities

ISSN

2055-7671

e-ISSN

2055-768X

Svazek periodika

37

Číslo periodika v rámci svazku

3

Stát vydavatele periodika

GB - Spojené království Velké Británie a Severního Irska

Počet stran výsledku

23

Strana od-do

693-715

Kód UT WoS článku

000763924000001

EID výsledku v databázi Scopus

2-s2.0-85141297978