{"title":"用于创建和分析来自社交网络用户的短电子消息文本数据库的软件工具","authors":"Alina Olegovna Loginova, Alexey Ivanovich Gorozhanov, Darya Viktorovna Aleynikova","doi":"10.30853/phil20230560","DOIUrl":null,"url":null,"abstract":"The research aims at developing an algorithm for creating and analyzing a text data bank of short electronic messages (posts) from social networks using free software tools. The scientific novelty lies in the fact that to solve such a problem, an interdisciplinary approach is used, taking into account the latest achievements of applied and mathematical linguistics and information security, with the involvement of the current regulatory framework. In the course of the work, according to the proposed graphical model, textual research material of ca. 1.5 MB was collected using the Web Scraper plug-in; a text data bank of short electronic messages was generated, converted into a CSV format suitable for further processing; a basic analysis of this data bank was carried out using PolyAnalyst free software package, which included such procedures as the extraction of terms, entities and keywords, sentiment analysis and determination of the subject matter of texts. As a result, the functionality of the created algorithm was proven, prospects for further research were identified – working with big text data and analyzing this data to find destructive content in them.","PeriodicalId":43335,"journal":{"name":"Theoretical and Practical Issues of Journalism","volume":"33 1","pages":"0"},"PeriodicalIF":0.6000,"publicationDate":"2023-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Software tools for creating and analyzing a text data bank of short electronic messages from social network users\",\"authors\":\"Alina Olegovna Loginova, Alexey Ivanovich Gorozhanov, Darya Viktorovna Aleynikova\",\"doi\":\"10.30853/phil20230560\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The research aims at developing an algorithm for creating and analyzing a text data bank of short electronic messages (posts) from social networks using free software tools. The scientific novelty lies in the fact that to solve such a problem, an interdisciplinary approach is used, taking into account the latest achievements of applied and mathematical linguistics and information security, with the involvement of the current regulatory framework. In the course of the work, according to the proposed graphical model, textual research material of ca. 1.5 MB was collected using the Web Scraper plug-in; a text data bank of short electronic messages was generated, converted into a CSV format suitable for further processing; a basic analysis of this data bank was carried out using PolyAnalyst free software package, which included such procedures as the extraction of terms, entities and keywords, sentiment analysis and determination of the subject matter of texts. As a result, the functionality of the created algorithm was proven, prospects for further research were identified – working with big text data and analyzing this data to find destructive content in them.\",\"PeriodicalId\":43335,\"journal\":{\"name\":\"Theoretical and Practical Issues of Journalism\",\"volume\":\"33 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.6000,\"publicationDate\":\"2023-10-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Theoretical and Practical Issues of Journalism\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.30853/phil20230560\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"COMMUNICATION\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Theoretical and Practical Issues of Journalism","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.30853/phil20230560","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMMUNICATION","Score":null,"Total":0}
Software tools for creating and analyzing a text data bank of short electronic messages from social network users
The research aims at developing an algorithm for creating and analyzing a text data bank of short electronic messages (posts) from social networks using free software tools. The scientific novelty lies in the fact that to solve such a problem, an interdisciplinary approach is used, taking into account the latest achievements of applied and mathematical linguistics and information security, with the involvement of the current regulatory framework. In the course of the work, according to the proposed graphical model, textual research material of ca. 1.5 MB was collected using the Web Scraper plug-in; a text data bank of short electronic messages was generated, converted into a CSV format suitable for further processing; a basic analysis of this data bank was carried out using PolyAnalyst free software package, which included such procedures as the extraction of terms, entities and keywords, sentiment analysis and determination of the subject matter of texts. As a result, the functionality of the created algorithm was proven, prospects for further research were identified – working with big text data and analyzing this data to find destructive content in them.