Research Seminar “Analytical Sociology and Big Data”

Bachelor 2022/2023

Type: Elective course (Sociology and Social Informatics)

Area of studies: Sociology

Delivered by: Department of Sociology

Where: Saint-Petersburg School of Social Sciences

When: 3 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

Full 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

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

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

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

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

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

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

Course Syllabus