Corpus of transcribed parliamentary speeches for authorship attribution and author profiling tasks

Kapočiūtė-Dzikienė, Jurgita; Utka, Andrius; Šarkutė, Ligita

doi:10.15388/klbt.2014.7674

Cited by 2 publications

(2 citation statements)

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“…query) efektyvumą [15] ir sprendžiant tekstų klasifikavimo (pagal žanrą, stilių ir pan. ), taip pat ir autoriaus identifikavimo uždavinius [19,7,27]. Tačiau kalbos mokslo požiūriu autorystės nustatymas nėra įdomus uždavinys, nebent siekiama nustatyti to paties teksto, kurį reikėjo kuo tiksliau atpasakoti, atpasakojimo autorių (plg.…”

Section: įVadasunclassified

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Analysis of Text Non-Homogeneity Using Markers

Lapėnaitė-Gedvilė¹,

Piaseckienė²,

Radavičius³

2015

LJS

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The aim of the paper is to assess the distributional non-homogeneity of texts in the usage of functional words andother linguistic units. Our empirical study is based on recommended school fiction works taken from a digital library athttp://ebiblioteka.mkp.emokykla.lt. Sets of frequent word forms, called markers, are made, and their frequency counts in blocks of 50successive sentences are calculated. The frequency counts of the markers show significant excess variability (overdispersion) withrespect to a text homogeneity model usually assumed in linguistics. For chosen markers, different kinds of hierarchical binomiallogistic regression models with the author's identifier, the block length and the frequency counts of the remaining markers as explanatory variables are fitted to the block data in order to explain the observed overdispersion of the markers chosen.

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“…3) arba pasitelkiant tikimybines kontekstines gramatikas. Nežinomi modelio parametrai, sąlyginės tikimybės, įvertinamos remiantis n-gramų (n iš eilės einančių žodžių) dažnumų statistika tekstyne [4,17,7].…”

Section: įVadasunclassified

Analysis of Text Non-Homogeneity Using Markers

Lapėnaitė-Gedvilė¹,

Piaseckienė²,

Radavičius³

2015

LJS

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Stylometric Analysis of Parliamentary Speeches: Gender Dimension

Mandravickaitė¹,

Krilavičius²

2017

Proceedings of the 6th Workshop on Balto-Slavic Natural Language Processing

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Relation between gender and language has been studied by many authors, however, there is still some uncertainty left regarding gender influence on language usage in the professional environment. Often, the studied data sets are too small or texts of individual authors are too short in order to capture differences of language usage wrt gender successfully. This study draws from a larger corpus of speeches transcripts of the Lithuanian Parliament (1990Parliament ( -2013 to explore language differences of political debates by gender via stylometric analysis. Experimental set up consists of stylistic features that indicate lexical style and do not require external linguistic tools, namely the most frequent words, in combination with unsupervised machine learning algorithms. Results show that gender differences in the language use remain in professional environment not only in usage of function words, preferred linguistic constructions, but in the presented topics as well.

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Corpus of transcribed parliamentary speeches for authorship attribution and author profiling tasks

Cited by 2 publications

References 22 publications

Analysis of Text Non-Homogeneity Using Markers

Analysis of Text Non-Homogeneity Using Markers

Stylometric Analysis of Parliamentary Speeches: Gender Dimension

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