Automated Classification of Potentially Insulting Speech Acts on Social Network Sites

Liliya Komalova, Anna Glazkova, Dmitry Morozov, Rostislav Epifanov, Leonid Motovskikh, Ekaterina Mayorova

Результат исследования: Публикации в книгах, отчётах, сборниках, трудах конференцийстатья в сборнике материалов конференциинаучнаярецензирование


Insulting speech acts have become the subject of public discussion in the media, social media, the basis for speculation in political communication, and a working concept in the legal environment. The present research article explores insulting speech acts on the social network site “VKontakte” aiming to develop an algorithm for automatic classification of text data. We conducted semantic analysis of the text of “Article 5.61” of the Code of Administrative Offenses of the Russian Federation, which made it possible to formulate inclusion criteria for formal classification. We used three common word embeddings models (BERT, ELMo, and fastText) on the original Russian language dataset consisting of 4596 annotated messages perceived as insulting speech acts. General findings argue that even in a specialized dataset the share of messages that meet criteria of inclusion is negligible. This indicates a low probability of going to court on the fact of an administrative offense under Article 5.61 based on speech communication on social network sites, even though such communication is public in nature and is automatically recorded in writing. Machine learning text classifier based on BERT model showed best performance.

Язык оригиналаанглийский
Название основной публикацииDigital Transformation and Global Society - 6th International Conference, DTGS 2021, Revised Selected Papers
РедакторыDaniel A. Alexandrov, Andrei V. Chugunov, Yury Kabanov, Olessia Koltsova, Ilya Musabirov, Sergei Pashakhin, Alexander V. Boukhanovsky, Andrei V. Chugunov
ИздательSpringer Science and Business Media Deutschland GmbH
Число страниц10
ISBN (электронное издание)978-3-030-93715-7
ISBN (печатное издание)978-3-030-93714-0
СостояниеОпубликовано - 2022
Событие6th International Conference on Digital Transformation and Global Society, DTGS 2021 - Virtual, Online
Продолжительность: 23 июн. 202125 июн. 2021

Серия публикаций

НазваниеCommunications in Computer and Information Science
Том1503 CCIS
ISSN (печатное издание)1865-0929
ISSN (электронное издание)1865-0937


Конференция6th International Conference on Digital Transformation and Global Society, DTGS 2021
ГородVirtual, Online

Предметные области OECD FOS+WOS



Подробные сведения о темах исследования «Automated Classification of Potentially Insulting Speech Acts on Social Network Sites». Вместе они формируют уникальный семантический отпечаток (fingerprint).