Text Mining technologies in sociological analysis (using the example of studying students`ideas about the mission of a modern university)

A. Pinchuk, S. Karepova, D. Tikhomirov
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Abstract

There are discussed in the article the possibilities of using Text Mining methods in the practice of analyzing the information received on the base of open questionnaire questions. The paper presents an example of unigrams and bigrams analysis, as well as the search for latent topic using thematic modeling. Empirical materials present the data of survey conducted in 2022, in which 929 students of one Moscow economics university took part. In the open question of the questionnaire, it was proposed to define the mission of the university. Information made it possible to get the subjective interpretation of the main significancy of higher education in modern conditions. The frequency analysis of unigrams, supplemented by a qualitative analysis of respondents’ statements, allowed reflecting the vocabulary of student discourse about the mission of the university. The articulation of bigrams was carried out on the basis of several statistical metrics, which made it possible to rank phrases and highlight a key set of concepts. The procedure revealed that in the perception of students, the priorities of the university are aimed at the transferring of professional knowledge and skills, in a broad sense – the training of qualified specialists. The social functions of the university, focused on meeting the needs of society and the state, are less pronounced in the conceptual interpretations of the interviewed students. At the next stage of the study the task of articulation and research of latent topics was put forward. The specific feature of thematic modeling is that the words combined into one topic reflect the distribution of words identified by the program, but not a topic that is literally understandable to a person. Taking into account the specifics of the method used, the authors demonstrated the results of search analysis in the practice of processing an open question. As it turned out, the keywords concentrated in the core of the main topics are mainly related to meeting the needs of the students themselves, leaving on the periphery of the verbalized definitions any understanding of the importance of the university as a platform for innovation, scientific research, entrepreneurial and other initiatives for the benefit of society and the country. The results of the presented research can be useful in rethinking the research tools of sociologists in the context of the active development of digital technologies, which requires testing new methods, understanding their real capabilities and limitations in solving the tasks of sociological research.
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社会学分析中的文本挖掘技术(以研究学生对现代大学使命的看法为例)
文章讨论了在分析开放式问卷所获信息的实践中使用文本挖掘方法的可能性。文章举例说明了单词和双词分析,以及使用主题建模寻找潜在主题的方法。实证材料介绍了 2022 年进行的调查数据,莫斯科一所经济大学的 929 名学生参加了调查。在调查问卷的开放性问题中,建议确定大学的使命。通过这些信息可以获得对现代高等教育主要意义的主观解释。在对受访者的陈述进行定性分析的基础上,对单词进行词频分析,从而反映出学生关于大学使命的话语词汇。根据几种统计指标进行了大词组分析,从而对短语进行了排序,并突出了一组关键概念。研究结果表明,在学生心目中,大学的首要任务是传授专业知识和技能,从广义上讲就是培养合格的专门人才。大学的社会职能侧重于满足社会和国家的需求,但在受访学生的概念解释中却不那么突出。在研究的下一阶段,提出了衔接和研究潜在主题的任务。主题建模的特点是,组合成一个主题的词语反映的是程序识别出的词语分布,而不是一个人从字面上可以理解的主题。考虑到所使用方法的特殊性,作者在处理一个开放性问题的实践中展示了搜索分析的结果。结果发现,集中在主要议题核心部分的关键词主要与满足学生自身需求有关,而对大学作为创新、科研、创业和其他造福社会和国家的举措平台的重要性的任何理解,都只停留在口头定义的外围。在数字技术积极发展的背景下,需要测试新的方法,了解其在解决社会学研究任务方面的真正能力和局限性,本文介绍的研究成果有助于重新思考社会学家的研究工具。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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