title: ÐÐ¿ÑÐµÐ´ÐµÐ»ÐµÐ½Ð¸Ðµ Ð°Ð²ÑÐ¾ÑÑÑÐ²Ð° ÐµÑÑÐµÑÑÐ²ÐµÐ½Ð½Ð¾-ÑÐ·ÑÐºÐ¾Ð²ÑÑ ÑÐµÐºÑÑÐ¾Ð² Ð² ÑÐ¾ÑÐ¸Ð°Ð»ÑÐ½ÑÑ ÑÐµÑÑÑ
title: Ð²ÑÐ¿ÑÑÐºÐ½Ð°Ñ ÐºÐ²Ð°Ð»Ð¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¾Ð½Ð½Ð°Ñ ÑÐ°Ð±Ð¾ÑÐ° Ð±Ð°ÐºÐ°Ð»Ð°Ð²ÑÐ°
titleType: Subtitle
title: Authorship Attribution of NaturalLanguage Texts in Social Networks
Creators: name: ÐÑÑÐ°Ð²ÐºÐ¾Ð², ÐÐ°Ð½Ð¸Ð¸Ð»
Publisher: name: Ð¡Ð°Ð½ÐºÑ-ÐÐµÑÐµÑÐ±ÑÑÐ³ÑÐºÐ¸Ð¹ Ð¿Ð¾Ð»Ð¸ÑÐµÑÐ½Ð¸ÑÐµÑÐºÐ¸Ð¹ ÑÐ½Ð¸Ð²ÐµÑÑÐ¸ÑÐµÑ ÐÐµÑÑÐ° ÐÐµÐ»Ð¸ÐºÐ¾Ð³Ð¾
Year: 2024
Subjects: ÐºÐ»Ð°ÑÑÐ¸ÑÐ¸ÐºÐ°ÑÐ¸Ñ ÑÐµÐºÑÑÐ°
Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ðµ Ð¾Ð±ÑÑÐµÐ½Ð¸Ðµ
Ð½Ð°Ð±Ð¾Ñ Ð´Ð°Ð½Ð½ÑÑ
Ð¾Ð±ÑÐ°Ð±Ð¾ÑÐºÐ° ÐµÑÑÐµÑÑÐ²ÐµÐ½Ð½Ð¾Ð³Ð¾ ÑÐ·ÑÐºÐ°
ÑÑÐ¸Ð»Ð¾Ð¼ÐµÑÑÐ¸ÑÐµÑÐºÐ¸Ðµ Ð¿ÑÐ¸Ð·Ð½Ð°ÐºÐ¸
ÑÐµÐºÑÑÐ¾Ð²ÑÐµ ÐºÐ¾ÑÐ¿ÑÑÐ°
text classification
machine learning
data set
natural language processing
stylometric features
text corps

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description: The topic of the final qualification work: "Authorship Attribution of Natural Language Texts in Social Networks" The aim of this work is to determine the optimal method for unambiguous identification of the author of natural language texts from the social network Telegram using modern machine learning algorithms and text vectorization methods. The subject of the research includes methods and algorithms of machine learning applied to author identification of natural language texts from social networks, including text vectorization and author classification. The tasks to be solved during the research are as follows: 1. Investigation of existing methods and machine learning algorithms applied to the task of author identification. 2. Preparation of the research object, containing normalized natural language texts from various authors in the social network Telegram. 3. Training of machine learning methods and algorithms for author identification of natural language texts. 4. Testing of machine learning methods and algorithms and evaluation of the obtained results. As a result of the work, it is expected to determine the most effective vectorization and classification methods for the authorship attribution task of texts from social networks. The analysis of stylometric features will additionally confirm the possibility of using these methods for authorship attribution of text.