From quantitative measurement to understanding public demand: Exploring non-survey methods in applied regional research

K. Ye. Petrov, E. N. Minchenko, V. S. Lapin
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Abstract

The article builds on the well-developed problem of studying trust in society towards social institutions, as well as between individuals. Currently, contact quantitative sociology faces a number of challenges, and the level of consent to participate in surveys is steadily falling. In order to reliably assess public opinion, non-contact tools for studying the digital environment are already required. The application of non-survey techniques for collecting big data using a pre-formed thesaurus allows us to select data for analysis and circumvent the problems associated with respondent recruitment. The application of SML approach to analyze digital publications of Russian-speaking users from Novosibirsk (more than 450 thousand publications) collected in 2020 has been considered. The combination of quantitative and qualitative methods allowed us to describe the audience and categorize the areas of public distrust and dissatisfaction. The application of this approach can be useful for managerial tasks aimed at increasing trust in society. Thus, the study is a valuable contribution to the development of modern sociology and its applied aspects.
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从定量测量到了解公众需求:探索应用区域研究中的非调查方法
本文建立在研究社会对社会机构以及个人之间的信任这一成熟问题的基础上。目前,接触定量社会学面临着诸多挑战,参与调查的同意程度正在稳步下降。为了可靠地评估民意,已经需要研究数字环境的非接触式工具。使用预先形成的词库来收集大数据的非调查技术的应用使我们能够选择数据进行分析,并规避与受访者招募相关的问题。考虑应用SML方法分析2020年收集的新西伯利亚俄语用户的数字出版物(超过45万份出版物)。定量和定性方法的结合使我们能够描述听众,并对公众不信任和不满的领域进行分类。这种方法的应用对旨在增加社会信任的管理任务是有用的。因此,该研究对现代社会学及其应用的发展作出了宝贵的贡献。
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审稿时长
8 weeks
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