maisМоделирование и анализ информационных системModeling and Analysis of Information Systems1818-10152313-5417Yaroslavl State University10.18255/1818-1015-2021-3-260-279mais-1527Research ArticleTheory of DataАнализ влияния стилометрических характеристик разного уровня на верификацию авторов художественных произведенийAnalysis of the Impact of the Stylometric Characteristics of Different Levels for the Verification of Authors of the Prosehttps://orcid.org/0000-0001-7429-3529МанаховаАлла МихайловнаManakhovaAlla Mikhajlovna

MSc student.

14 Sovetskaya str., Yaroslavl 150003

MSc student.

14 Sovetskaya str., Yaroslavl 150003

al.mnkhv@yandex.ruhttps://orcid.org/0000-0002-6137-8643ЛагутинаНадежда СтаниславовнаLagutinaNadezhda Stanislavovna

Доцент, кандидат физико-математических наук.

Ул. Советская, д. 14, Ярославль, 150003

Associate Professor, PhD in Physics and Mathematics.

14 Sovetskaya str., Yaroslavl 150003

lagutinans@rambler.ruЯрославский государственный университет им. П.Г. ДемидоваРоссияP.G. Demidov Yaroslavl State UniversityRussian Federation202112102021283260279Copyright © Манахова А.М., Лагутина Н.С., 20212021Манахова А.М., Лагутина Н.С.Manakhova A.M., Lagutina N.S.Данная работа распространяется под лицензией Creative Commons Attribution 4.0.This work is licensed under a Creative Commons Attribution 4.0 License.https://www.mais-journal.ru/jour/article/view/1527

Данная статья посвящена анализу влияния различных комбинаций стилометрических характеристик разного уровня на качество верификации авторства русских, английских и французских прозаических текстов. Исследование проводилось как для низкоуровневых стилометрических характеристик, основанных на словах и символах, так и для более высокоуровневых – структурных.

Подсчёт всех стилометрических характеристик был выполнен автоматически с помощью программы ProseRhythmDetector. Такой подход позволил провести анализ произведений большого объёма и многих писателей одновременно. В ходе работы каждому тексту были сопоставлены векторы стилометрических характеристик уровня символов, слов и структуры. При проведении экспериментов наборы параметров этих трёх уровней были скомбинированы между собой всеми возможными способами. Полученные векторы стилометрических характеристик были поданы на вход различным классификаторам для выполнения верификации и выявления наиболее подходящего классификатора для решения поставленной задачи. Лучшие результаты были получены с помощью классификатора AdaBoost. Средняя F-мера для всех языков оказалась более 92%. Детальные оценки качества верификации приведены для каждого автора и проанализированы. Использование высокоуровневых стилометрических характеристик, в частности, частоты использования N-грамм POS-тегов открывает перспективу более детального анализа стиля того или иного автора. Результаты экспериментов показывают, что при соединении характеристик уровня структуры с характеристиками уровня слов и/или символов получаются наиболее точные результаты верификации авторства для художественных текстов на русском, английском и французском языках. Дополнительно авторам удалось сделать вывод о разной степени влияния стилометрических характеристик на качество верификации авторства для различных языков.

This article is dedicated to the analysis of various stylometric characteristics combinations of different levels for the quality of verification of authorship of Russian, English and French prose texts. The research was carried out for both low-level stylometric characteristics based on words and symbols and higher-level structural characteristics.

All stylometric characteristics were calculated automatically with the help of the ProseRhythmDetector program. This approach gave a possibility to analyze the works of a large volume and of many writers at the same time. During the work, vectors of stylometric characteristics of the level of symbols, words and structure were compared to each text. During the experiments, the sets of parameters of these three levels were combined with each other in all possible ways. The resulting vectors of stylometric characteristics were applied to the input of various classifiers to perform verification and identify the most appropriate classifier for solving the problem. The best results were obtained with the help of the AdaBoost classifier. The average F-score for all languages turned out to be more than 92 %. Detailed assessments of the quality of verification are given and analyzed for each author. Use of high-level stylometric characteristics, in particular, frequency of using N-grams of POS tags, offers the prospect of a more detailed analysis of the style of one or another author. The results of the experiments show that when the characteristics of the structure level are combined with the characteristics of the level of words and / or symbols, the most accurate results of verification of authorship for literary texts in Russian, English and French are obtained. Additionally, the authors were able to conclude about a different degree of impact of stylometric characteristics for the quality of verification of authorship for different languages.

стилометриястилометрические характеристикиверификация авторстваобработка естественного языкаstylometrystylometric characteristicsauthorship verificationnatural language processingReferencesN. P. Tuchkova and O. M. Ataeva, “Podhody k izvlecheniyu znanij v nauchnyh predmetnyh oblastyah”, Informacionnye i matematicheskie tekhnologii v nauke i upravlenii, no. 2 (18), pp. 5–18, 2020.N. P. Tuchkova and O. M. Ataeva, “Podhody k izvlecheniyu znanij v nauchnyh predmetnyh oblastyah”, Informacionnye i matematicheskie tekhnologii v nauke i upravlenii, no. 2 (18), pp. 5–18, 2020.A. Altamimi, N. Clarke, S. Furnell, and F. Li, “Multi-platform authorship verification”, in Proceedings of the Third Central European Cybersecurity Conference, 2019, pp. 1–7.A. Altamimi, N. Clarke, S. Furnell, and F. Li, “Multi-platform authorship verification”, in Proceedings of the Third Central European Cybersecurity Conference, 2019, pp. 1–7.O. Halvani, L. Graner, and R. Regev, “Taveer: An interpretable topic-agnostic authorship verification method”, in Proceedings of the 15th International Conference on Availability, Reliability and Security, 2020, pp. 1–10.O. Halvani, L. Graner, and R. Regev, “Taveer: An interpretable topic-agnostic authorship verification method”, in Proceedings of the 15th International Conference on Availability, Reliability and Security, 2020, pp. 1–10.M. Kestemont, G. Martens, and T. Ries, “A computational approach to authorship verification of johann wolfgang goethe’s contributions to the frankfurter gelehrte anzeigen (1772–73)”, Journal of European Periodical Studies, vol. 4, no. 1, pp. 115–143, 2019.M. Kestemont, G. Martens, and T. Ries, “A computational approach to authorship verification of johann wolfgang goethe’s contributions to the frankfurter gelehrte anzeigen (1772–73)”, Journal of European Periodical Studies, vol. 4, no. 1, pp. 115–143, 2019.S. Corbara, A. Moreo, F. Sebastiani, and M. Tavoni, “The epistle to cangrande through the lens of computational authorship verification”, in International Conference on Image Analysis and Processing, Springer, 2019, pp. 148–158.S. Corbara, A. Moreo, F. Sebastiani, and M. Tavoni, “The epistle to cangrande through the lens of computational authorship verification”, in International Conference on Image Analysis and Processing, Springer, 2019, pp. 148–158.V. A. Drozdov, “Ob avtorstve poemy ≪‘Ushshak-name≫ s tochki zreniya akademicheskogo vostokovedeniya i novejshih komp’yuternyh tekhnologij”, Orientalistika, vol. 3, no. 5, pp. 1360–1378, 2020.V. A. Drozdov, “Ob avtorstve poemy ≪‘Ushshak-name≫ s tochki zreniya akademicheskogo vostokovedeniya i novejshih komp’yuternyh tekhnologij”, Orientalistika, vol. 3, no. 5, pp. 1360–1378, 2020.M. Kestemont, E. Manjavacas, I. Markov, J. Bevendorff, M. Wiegmann, E. Stamatatos, M. Potthast, and B. Stein, “Overview of the cross-domain authorship verification task at pan 2020”, in CLEF, 2020.M. Kestemont, E. Manjavacas, I. Markov, J. Bevendorff, M. Wiegmann, E. Stamatatos, M. Potthast, and B. Stein, “Overview of the cross-domain authorship verification task at pan 2020”, in CLEF, 2020.N. Potha and E. Stamatatos, “Intrinsic author verification using topic modeling”, in Proceedings of the 10th Hellenic Conference on Artificial Intelligence, ACM, 2018, pp. 1–7.N. Potha and E. Stamatatos, “Intrinsic author verification using topic modeling”, in Proceedings of the 10th Hellenic Conference on Artificial Intelligence, ACM, 2018, pp. 1–7.S. Adamovic, V. Miskovic, M. Milosavljevic, M. Sarac, and M. Veinovic, “Automated language-independent authorship verification (for indo-european languages)”, Journal of the Association for Information Science and Technology, vol. 70, no. 8, pp. 858–871, 2019.S. Adamovic, V. Miskovic, M. Milosavljevic, M. Sarac, and M. Veinovic, “Automated language-independent authorship verification (for indo-european languages)”, Journal of the Association for Information Science and Technology, vol. 70, no. 8, pp. 858–871, 2019.B. Boenninghoff, S. Hessler, D. Kolossa, and R. M. Nickel, “Explainable authorship verification in social media via attention-based similarity learning”, in 2019 IEEE International Conference on Big Data (Big Data), IEEE, 2019, pp. 36–45.B. Boenninghoff, S. Hessler, D. Kolossa, and R. M. Nickel, “Explainable authorship verification in social media via attention-based similarity learning”, in 2019 IEEE International Conference on Big Data (Big Data), IEEE, 2019, pp. 36–45.N. E. Benzebouchi, N. Azizi, M. Aldwairi, and N. Farah, “Multi-classifier system for authorship verification task using word embeddings”, in 2018 2nd International Conference on Natural Language and Speech Processing (ICNLSP), IEEE, 2018, pp. 1–6.N. E. Benzebouchi, N. Azizi, M. Aldwairi, and N. Farah, “Multi-classifier system for authorship verification task using word embeddings”, in 2018 2nd International Conference on Natural Language and Speech Processing (ICNLSP), IEEE, 2018, pp. 1–6.J. S. Li, L.-C. Chen, J. V. Monaco, P. Singh, and C. C. Tappert, “A comparison of classifiers and features for authorship authentication of social networking messages”, Concurrency and Computation: Practice and Experience, vol. 29, no. 14, e3918, 2017.J. S. Li, L.-C. Chen, J. V. Monaco, P. Singh, and C. C. Tappert, “A comparison of classifiers and features for authorship authentication of social networking messages”, Concurrency and Computation: Practice and Experience, vol. 29, no. 14, e3918, 2017.E. Tuccinardi, “An application of a profile-based method for authorship verification: Investigating the authenticity of pliny the younger’s letter to trajan concerning the christians”, Digital Scholarship in the Humanities, vol. 32, no. 2, pp. 435–447, 2017.E. Tuccinardi, “An application of a profile-based method for authorship verification: Investigating the authenticity of pliny the younger’s letter to trajan concerning the christians”, Digital Scholarship in the Humanities, vol. 32, no. 2, pp. 435–447, 2017.P. B. Reddy, T. M. Mohan, P. V. K. Raja, and T. R. Reddy, “A novel approach for authorship verification”, in Data Engineering and Communication Technology, Springer, 2020, pp. 441–448.P. B. Reddy, T. M. Mohan, P. V. K. Raja, and T. R. Reddy, “A novel approach for authorship verification”, in Data Engineering and Communication Technology, Springer, 2020, pp. 441–448.E. Castillo, O. Cervantes, and D. Vilarino, “Authorship verification using a graph knowledge discovery approach”, Journal of Intelligent & Fuzzy Systems, vol. 36, no. 6, pp. 6075–6087, 2019.E. Castillo, O. Cervantes, and D. Vilarino, “Authorship verification using a graph knowledge discovery approach”, Journal of Intelligent & Fuzzy Systems, vol. 36, no. 6, pp. 6075–6087, 2019.H. Ahmed, “The role of linguistic feature categories in authorship verification”, Procedia computer science, vol. 142, pp. 214–221, 2018.H. Ahmed, “The role of linguistic feature categories in authorship verification”, Procedia computer science, vol. 142, pp. 214–221, 2018.M. A. Al-Khatib and J. K. Al-qaoud, “Authorship verification of opinion articles in online newspapers using the idiolect of author: A comparative study”, Information, Communication & Society, pp. 1–19, 2020.M. A. Al-Khatib and J. K. Al-qaoud, “Authorship verification of opinion articles in online newspapers using the idiolect of author: A comparative study”, Information, Communication & Society, pp. 1–19, 2020.K. Lagutina, N. Lagutina, E. Boychuk, I. Vorontsova, E. Shliakhtina, O. Belyaeva, and I. Paramonov, “A survey on stylometric text features”, in Proceedings of the 25th Conference of Open Innovations Association (FRUCT), IEEE, 2019, pp. 184–195.K. Lagutina, N. Lagutina, E. Boychuk, I. Vorontsova, E. Shliakhtina, O. Belyaeva, and I. Paramonov, “A survey on stylometric text features”, in Proceedings of the 25th Conference of Open Innovations Association (FRUCT), IEEE, 2019, pp. 184–195.Y. Polin, T. Zudilova, I. Ananchenko, and T. Vojtyuk, “Derevya reshenij v zadachah klassifikacii: osobennosti primeneniya i metody povysheniya kachestva klassifikacii”, Sovremennye naukoemkie tekhnologii, no. 9, pp. 59–63, 2020.Y. Polin, T. Zudilova, I. Ananchenko, and T. Vojtyuk, “Derevya reshenij v zadachah klassifikacii: osobennosti primeneniya i metody povysheniya kachestva klassifikacii”, Sovremennye naukoemkie tekhnologii, no. 9, pp. 59–63, 2020.B. Xu, X. Guo, Y. Ye, and J. Cheng, “An improved random forest classifier for text categorization.”, JCP, vol. 7, no. 12, pp. 2913–2920, 2012.B. Xu, X. Guo, Y. Ye, and J. Cheng, “An improved random forest classifier for text categorization.”, JCP, vol. 7, no. 12, pp. 2913–2920, 2012.S.-B. Kim, K.-S. Han, H.-C. Rim, and S. H. Myaeng, “Some effective techniques for naive bayes text classification”, IEEE transactions on knowledge and data engineering, vol. 18, no. 11, pp. 1457–1466, 2006.S.-B. Kim, K.-S. Han, H.-C. Rim, and S. H. Myaeng, “Some effective techniques for naive bayes text classification”, IEEE transactions on knowledge and data engineering, vol. 18, no. 11, pp. 1457–1466, 2006.K. Lagutina, A. Poletaev, N. Lagutina, E. Boychuk, and I. Paramonov, “Automatic extraction of rhythm figures and analysis of their dynamics in prose of 19th-21st centuries”, in Proceedings of the 26th Conference of Open Innovations Association (FRUCT), IEEE, 2020, pp. 247–255.K. Lagutina, A. Poletaev, N. Lagutina, E. Boychuk, and I. Paramonov, “Automatic extraction of rhythm figures and analysis of their dynamics in prose of 19th-21st centuries”, in Proceedings of the 26th Conference of Open Innovations Association (FRUCT), IEEE, 2020, pp. 247–255.

The authors declare that there are no conflicts of interest present.