Научно-исследовательский семинар "Аналитическая социология и большие данные"
- to provide students with skills necessary for conducting social research based on big data analysis
- understand modern features and issues of big data analytics; should learn basic methodological principles and major methods applicable for big data analysis
- be able to apply the methods of analytical sociology and social statistics to the analysis of big data; to use basic rules of statistical inference; to employ major sociological concepts as instruments of sociological research
- 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
- Introduction to analytical sociology and applicationsBasic principles of analytical sociology. Key authors in the field of analytical sociology
- Sources of big data; quality of dataTypology of data sources. Principles of data collection. Big data quality assessment
- Literature review: basic principles and search for the articlesBasic principles. Logic of literature review. Sources of literature
- Operationalization of theoretical concepts and measurementOperationalization. Measurement principles in sociology
- Research design for the big data analysisTypology of research designs. Most common research designs for big data researches
- Studying stratification and intergenerational mobility using big dataGeneral idea of social stratification analysis. Big data sources. Example article
- Social movements analysis using big dataGeneral idea of social movements analysis. Big data sources. Example article
- Presentation of the research resultsGeneral principles of good presentation. Practical session
- Participation in class discussions
- In-class assignmentsIn-class assignments grade will be calculated as an average score for all types of written activities during the seminars.
- Presentation of their individual projectPresentation of the individual project includes final presentation on the topic of student’s thesis and should represent a solid presentation of research framework, literature review, data description and preliminary analysis.
- Final examFinal exam will consist of a set of questions related to student’s thesis. Answer to all questions will be cross-graded by several instructors and the final grade for the exam will be calculated as an average score for all grades for all exam items. The grade for the final exam is rounded according to algebra rules.
- Interim assessment (3 module)0.25 * Final exam + 0.25 * In-class assignments + 0.25 * Participation in class discussions + 0.25 * Presentation of their individual project
- 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
- 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