Bachelor
2025/2026
Applied Software
Type:
Elective course (Sociology and Social Informatics)
Delivered by:
Department of Sociology
When:
3 year, 2, 3 module
Open to:
students of one campus
Language:
English
ECTS credits:
3
Contact hours:
40
Course Syllabus
Abstract
This course integrates mathematical methods and models to extract, analyze, and visualize data, ultimately addressing professional problems and fostering innovative approaches to data analysis. It also involves the creation of analytical materials applicable in both applied and academic fields of sociology. The primary objective of the course is to enhance students' skills in data handling and to develop technologies for data processing, visualization, and intelligence analysis. Within the framework of this discipline, students will develop competencies in utilizing artificial intelligence (AI) tools to collect, analyze, and interpret quantitative data. This includes setting research tasks and testing hypotheses using quantitative methodologies. The course will cover the foundational methodology of bibliometric data analysis, guiding students through the process from data acquisition to result interpretation. Students will learn to leverage information resources and specialized software to prepare analytical literature reviews and analyze media data. A key focus of the course will be on visualizing online bibliometric data through mapping the research field. Various tools for bibliographic analysis will be explored, including the R programming language (bibliometrix), VOSViewer, and CitNetExplorer. Additionally, students will examine information retrieval strategies and principles for compiling literature reviews, encompassing citation practices. A substantial portion of the course is dedicated to the principles of working with bibliographic databases, including the creation of search queries to collect citation data, the use of built-in tools to analyze scientific trends, and the exportation of data from databases. A separate section will focus on working with news databases. The final chapter of the course will discuss strategies for literature analysis and review writing. Using the acquired data, students will practice constructing citation maps in programs designed for visualizing the scientific landscape and will write a literature review on a selected topic.