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A content analysis software system for efficient monitoring and detection of hate speech in online media

- Krylova-Grek, Yuliya (orcid.org/0000-0002-2377-3781) and Burov, O. Yu. (orcid.org/0000-0003-0733-1120) (2024) A content analysis software system for efficient monitoring and detection of hate speech in online media Proceedings of the 11th Workshop on Cloud Technologies in Education (CTE 2023). Kryvyi Rih, Ukraine, December 22, 2023 (3679). pp. 224-233. ISSN 1613-0073

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Abstract

This paper presents the results of interdisciplinary project that is a combination of computer program and psycholinguistic approach to media study. In the research we presented the programs that can be used for monitoring and analysis of media content to identify hate speech at its early stage. The aims of research were the following: 1) develop content analysis program for monitoring Russian media outlets; 2) apply the psycholinguistic approach for identifying hidden and manipulative hate speech. In the research there were used two types of content-analysis: quantitative and qualitative. Quantitative content analysis was conducted with computer program that was developed to select publication that could have contained hate speech. For qualitative content analysis the psycholinguistic method of text analysis was used. The method applies for identification methods and tolls that journalists use to incriminate hidden and manipulative hate speech. It is hypothesized that programs of content-analysis help to optimize work and makes it less time-consuming and more effective for analyst, journalists and other specialists who involved into media study. Methods. Quantitative content analysis, psycholinguistic method of qualitative content-analysis. Quantitative content analysis was developed with Python programming language. The publications were selected according to the key words, periods of search (month) and the name of outlet. The list of key words includes words that are used in media for discrimination, dehumanization, and marginalization of objects of hate. Implementation such a program helped to reduce time of monitoring of media outlets. The qualitative content-analysis was conducted with the authors’ psycholinguistic method of text analysis that can be applied for analyzing media texts. The programs of content analysis were applied within the project “Hate Speech in Online Media Publicizing Events in Crimea”. The results were published in a data analysis report on spreading the hate speech in the Russian language media communicating the armed Ukraine – Russia conflict and events related to it in Crimea on a regular base (December 2020 – May 2021). The research showed that the content analysis programs used in the project are useful tools for systematizing and processing data in humanities research and can be used by a wide range of specialist who have deal with collection and processing of information (media, communication, human rights and so on).

Item Type: Article
Keywords: content-analysis, media, hate speech, text
Subjects: Science and knowledge. Organization. Computer science. Information. Documentation. Librarianship. Institutions. Publications > 00 Prolegomena. Fundamentals of knowledge and culture. Propaedeutics > 004 Computer science and technology. Computing. Data processing > 004.7 Computer communication. Computer networks > 004.77 General networking applications and services
Science and knowledge. Organization. Computer science. Information. Documentation. Librarianship. Institutions. Publications > 3 Social Sciences > 32 Politics
Science and knowledge. Organization. Computer science. Information. Documentation. Librarianship. Institutions. Publications > 8 Language. Linguistics. Literature > 80 General questions relating to both linguistics and literature. Philology
Divisions: Institute for Digitalisation of Education > Department of Technologies of Open Learning Environment
Depositing User: с.д/п.н.с. Oleksandr Burov
Date Deposited: 01 Oct 2024 06:47
Last Modified: 01 Oct 2024 06:47
URI: https://lib.iitta.gov.ua/id/eprint/742533

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