Selecting text features relevant for authorship attribution | Vestnik Tomskogo gosudarstvennogo universiteta. Filologiya – Tomsk State University Journal of Philology. 2013. № 6 (26). DOI: 10.17223/19986645/26/4

Selecting text features relevant for authorship attribution

The article discusses the problem of text features that are relevant for the tasks of the author attribution of the text. Analysis of the works in this area demonstrates the efficiency of such features as bigram and trigram symbols and words, functional words, distribution of words by parts of speech, most frequent words, punctuation marks, word length distribution and length of sentences. These are formal and formal-semantic linguistic elements of all the subsystems of the language system. The most commonly used diagnostic parameters in authorship expert review are formal features of the lower subsystems of the language system. Usually the speaker is not aware of these signs in the generation of speech. These elements are easy to distinguish for a programmer who does not have a special degree in Linguistics. In identifying the statistical patterns of use of such elements small amounts of text may be involved. Elements of formal-semantic segmentation of speech are less involved as a diagnostic parameter. The author of the text may deliberately simulate these parameters. The programmer has to use pre-tagged texts, a special linguistic analysis of texts and a specialised corpus are needed. In identifying the statistical patterns of use of such elements big amounts of text may be involved. The authors name features of text that can be diagnosing only in certain types of texts. Idiosyncratic features (lexical, grammatical errors, etc.) are not relevant in the edited and corrected texts, the use of metadata is applicable to computer texts, etc. The authors note the unsolved problem of context independent features of the text. Many of the results of authorship attribution were obtained in the analysis of texts in English and other Indo-European languages. The relevance of these features for Russian texts is topical. It is especially necessary to identify the relevant grammatical features. The Russian authorship attribution tested the methodology on the material of literary texts. It is now necessary to identify (define) the composition (set) of context-independent features and attributes that are relevant for analysing texts of a certain type. Effective use (application) of the morphological and syntactic text features is possible only on the basis of linguistic text markup. The Russian authorship attribution needs a specialised linguistically marked Russian corpus.

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Keywords

data mining, computer science, interdisciplinary methods of research, stylometry, authorship expert review, авторская атрибуция текста, интеллектуальный анализ данных, информатика, междисциплинарные методы исследования, стилометрия, автороведческая экспертиза

Authors

Name	Organization	E-mail
Rezanova Zoya I.	Tomsk State University; Tomsk Polytechnic University	resso@rambler.ru; resso@mail.tsu.ru; rezanovazi@mail.ru
Romanov Alexandr S.	Tomsk State University of Control Systems and Radioelectronics	alexx.romanov@gmail.com
Meshcheryakov Roman V.	Tomsk State University of Control Systems and Radioelectronics	mrv@ieee.org

Всего: 3

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