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

IF 0.6 Q3 COMMUNICATION Theoretical and Practical Issues of Journalism Pub Date : 2023-10-25 DOI:10.30853/phil20230560
Alina Olegovna Loginova, Alexey Ivanovich Gorozhanov, Darya Viktorovna Aleynikova
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引用次数: 0

摘要

该研究旨在开发一种算法,用于使用免费软件工具创建和分析来自社交网络的短电子信息(帖子)文本数据库。科学的新颖性在于,为了解决这样一个问题,采用了跨学科的方法,考虑到应用和数学语言学和信息安全的最新成就,并涉及当前的监管框架。在工作过程中,根据提出的图形化模型,使用Web Scraper插件收集了约1.5 MB的考证资料;生成短电子讯息的文本资料库,并将其转换为适合进一步处理的CSV格式;使用PolyAnalyst免费软件包对该数据库进行基础分析,包括术语、实体和关键词的提取、情感分析和文本主题的确定等步骤。结果,所创建的算法的功能得到了证明,并确定了进一步研究的前景-处理大文本数据并分析这些数据以找出其中的破坏性内容。
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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.
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