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Regular version of the site
Bachelor 2021/2022

Research Seminar “Analytical Sociology and Big Data”

Category 'Best Course for Broadening Horizons and Diversity of Knowledge and Skills'
Category 'Best Course for New Knowledge and Skills'
Type: Elective course (Sociology and Social Informatics)
Area of studies: Sociology
When: 2 year, 1-4 module
Mode of studies: offline
Open to: students of all HSE University campuses
Instructors: Daniil A. Alexandrov, Valeria A. Ivaniushina, Olesya Vólchenko
Language: English
ECTS credits: 4
Contact hours: 42

Course Syllabus

Abstract

The purpose of the course is to provide students with skills necessary for conducting social research based on big data analysis. During the course different features of analytical approach towards big data will be covered as well as a variety of examples of reports and articles relevant for the field. The seminar is intended for students who have previously attended research seminars of the BA in Sociology and Social Informatics in the previous years.
Learning Objectives

Learning Objectives

  • be able to read and critically discuss articles from the field of the big data analysis and conduct empirical research using different sources of the data.
Expected Learning Outcomes

Expected Learning Outcomes

  • be able to apply the methods of analytical sociology and social statistics to the analysis of big data
  • employ major sociological concepts as instruments of sociological research
  • learn basic methodological principles and major methods applicable for big data analysis
  • read and discuss journal articles and book chapters; participate in group research projects; give presentations on their research projects and topics of their interest
  • understand modern features and issues of big data analytics
  • use basic rules of statistical inference
Course Contents

Course Contents

  • Introduction to analytical sociology and applications
  • Sources of big data; quality of data
  • Research design for the big data analysis
  • Studying stratification and intergenerational mobility using big data
  • Social movements analysis using big data
  • Educational research using big data
  • Health research using big data
  • Ethical issues of the big data research
Assessment Elements

Assessment Elements

  • non-blocking Participation in class discussions
  • non-blocking Written assignments
    In-class assignments grade will be calculated as an average score for all types of written activities during the seminars.
  • non-blocking Presentation of the individual project
    Presentation of the individual project includes final presentation on the topic of student’s course work and should represent a solid presentation of research framework, literature review, data description, data analysis and main conclusions.
  • non-blocking Participation in perusall discussion
Interim Assessment

Interim Assessment

  • 2021/2022 4th module
    0.3 * Participation in class discussions + 0.3 * Presentation of the individual project + 0.2 * Written assignments + 0.2 * Participation in perusall discussion
  • 2022/2023 4th module
    0.3 * Presentation of the individual project + 0.2 * Participation in perusall discussion + 0.3 * Participation in class discussions + 0.2 * Written assignments
  • 2023/2024 3rd module
    -
Bibliography

Bibliography

Recommended Core Bibliography

  • Van Rijmenam, M. (2014). Think Bigger : Developing a Successful Big Data Strategy for Your Business. New York: AMACOM. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=686831

Recommended Additional Bibliography

  • Manzo, G. (2014). Analytical Sociology : Actions and Networks. Hoboken: Wiley. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=714658

Authors

  • IVANYUSHINA VALERIYA ALEKSANDROVNA
  • ALEKSANDROV DANIIL ALEKSANDROVICH
  • TSVETKOVA EKATERINA ANDREEVNA
  • VOLCHENKO OLESYA VIKTOROVNA