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Бакалаврская программа «Социология и социальная информатика»

Research Seminar “Analytical Sociology and Big Data”

2022/2023
Учебный год
ENG
Обучение ведется на английском языке
4
Кредиты
Статус:
Курс по выбору
Когда читается:
2-й курс, 1-4 модуль

Преподаватели

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 Written assignments
    In-class assignments grade will be calculated as an average score for all types of written activities during the seminars.
  • non-blocking Participation in class discussions
  • non-blocking Participation in perusall discussion
  • 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.
Interim Assessment

Interim Assessment

  • 2022/2023 4th module
    0.2 * Participation in perusall discussion + 0.3 * Presentation of the individual project + 0.2 * Written assignments + 0.3 * Participation in class discussions
  • 2023/2024 4th module
    -
  • 2024/2025 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