{"title":"A Method for Identifying Potential Internal Violators Based on the Analysis of the Tone of Messages from Users of Social Networks","authors":"A. Martyshkin, D. Pashchenko","doi":"10.1109/RusAutoCon52004.2021.9537338","DOIUrl":null,"url":null,"abstract":"The purpose of the work is to study social network users as potential internal violators through the analysis of the tonality of text messages. To achieve the goal, the following tasks have been set and solved: 1) Determine the basics of sentiment analysis for text messages; 2) Highlight the lack of existing methods for identifying internal violators; 3) Propose and develop a preventive method for identifying potential internal violators based on the analysis of the sentiment of text messages. An analysis of the subject area of the study was carried out, which included a review of existing methods for identifying insiders. The paper analyzes internal violators with the identification of potential ones, and also considers the means of processing natural languages and identifies approaches to the classification of the tonality of the text.. The article solves the problem of developing a method for identifying potential internal offenders, based on the analysis of the sentiment of text messages. An analysis was made of the funds allocated and the methods that are appropriate to achieve the research objective. The developed method is described. As a result of the study, a method was proposed that allows one to identify potential internal offenders by analyzing the sentiment of their text messages on social networks.","PeriodicalId":106150,"journal":{"name":"2021 International Russian Automation Conference (RusAutoCon)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 International Russian Automation Conference (RusAutoCon)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/RusAutoCon52004.2021.9537338","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
The purpose of the work is to study social network users as potential internal violators through the analysis of the tonality of text messages. To achieve the goal, the following tasks have been set and solved: 1) Determine the basics of sentiment analysis for text messages; 2) Highlight the lack of existing methods for identifying internal violators; 3) Propose and develop a preventive method for identifying potential internal violators based on the analysis of the sentiment of text messages. An analysis of the subject area of the study was carried out, which included a review of existing methods for identifying insiders. The paper analyzes internal violators with the identification of potential ones, and also considers the means of processing natural languages and identifies approaches to the classification of the tonality of the text.. The article solves the problem of developing a method for identifying potential internal offenders, based on the analysis of the sentiment of text messages. An analysis was made of the funds allocated and the methods that are appropriate to achieve the research objective. The developed method is described. As a result of the study, a method was proposed that allows one to identify potential internal offenders by analyzing the sentiment of their text messages on social networks.