Applied Software

2025/2026

Academic Year

ENG

Instruction in English

Delivered at:

Department of Sociology

Course type:

Elective course

When:

3 year, 2, 3 module

Instructor

Moreva, Yulia

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.

Learning Objectives

• learn how to visualize bibliometric data through mapping the research field
• learn how to use bibliometric data to write a literature review on a selected topic

Expected Learning Outcomes

• Find relevant data and academic literature
• Use the results of analysis to prepare literature reviews
• Work with bibliographic databases
• Apply network methods to analyze citation data

Course Contents

• Introduction
• Principles of working with citation databases
• Creating bibliometric maps
• Proper citation. Instruments for bibliographic data storage and systematization.
• Principles of literature review organization

Assessment Elements

• In-class participation
• Project Proposal
• Literature review
• Midterm test

Interim Assessment

• 2025/2026 3rd module
  0.15 * In-class participation + 0.15 * In-class participation + 0.2 * Literature review + 0.1 * Midterm test + 0.2 * Project Proposal + 0.2 * Project Proposal

Bibliography

Recommended Core Bibliography

• Eck, N. J. P. (Nees J. van, & Waltman, L. (Ludo). (2010). Software survey: VOSviewer, a computer program for bibliometric mapping. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsbas&AN=edsbas.3AC7DCD5
• Wang, G. T., & Park, K. (2016). Student Research and Report Writing : From Topic Selection to the Complete Paper. West Sussex: Wiley-Blackwell. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1108252

Recommended Additional Bibliography

• Nicola De Bellis. (2009). Bibliometrics and Citation Analysis : From the Science Citation Index to Cybermetrics. Scarecrow Press.
• Wang, J., Veugelers, R., & Stephan, P. (2017). Bias against novelty in science: A cautionary tale for users of bibliometric indicators. Research Policy, (8), 1416. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsrep&AN=edsrep.a.eee.respol.v46y2017i8p1416.1436
• Yves Gingras. (2016). Bibliometrics and Research Evaluation : Uses and Abuses. The MIT Press.

Authors

• MOREVA IULIIA EVGENEVNA