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Бакалаврская программа «Социология и социальная информатика»

07
Апрель

Special Topics of Social Informatics

2023/2024
Учебный год
ENG
Обучение ведется на английском языке
6
Кредиты
Статус:
Курс по выбору
Когда читается:
4-й курс, 3 модуль

Course Syllabus

Abstract

We will build our work around the understanding of how statistics and computation work in social, applied and CS research, focusing on acquiring deeper understanding of statistical inference based on observational and experimental data and focusing on “big data” research using digital methods. If you are planning to do a quantitative study for your thesis, this course will help you to think about suitable research design early on, hopefully leading to better results and less issues. If you think on continuing your career or education in quantitative directions – from high-profile MSc programmes in quantitative social science, data, business analytics or UX analytics, this course might help you to build necessary conceptual and computational foundation in these areas. We will use simulations, pictures and intuition more than math and use online course materials and extra reading as a backbone for our discussion and simulations, so this course should be accessible for those without Data Science minor or alternative experience. However, the course will require large amount of independent work.
Learning Objectives

Learning Objectives

  • equipping students with tools to transform ideas and apply theories to practice, using modern (“digital”) research methods and tools of social informatics
Expected Learning Outcomes

Expected Learning Outcomes

  • Applies modern social research methods and models to study behavior, decision making and social phenomena using tools of social informatics
  • Creates research proposals describing possible application of modern research methods and tools of social informatics to the areas of choice, presents and discusses it
  • Formulates goals and research questions to observational and experimental studies using tools of social informatics
Course Contents

Course Contents

  • Introduction to the course. Digital research design. Statistics, Experiment, Simulation
  • Observing Behavior using Digital Data
  • Research Questions and Methods. Experiments
  • Human Computation & Citizen Science
  • Modern statistical inference
  • Digital Research Designs
Assessment Elements

Assessment Elements

  • non-blocking Peer review of research design
  • non-blocking Online Course Tests
Interim Assessment

Interim Assessment

  • 2023/2024 3rd module
    0.3 * Peer review of research design + 0.7 * Online Course Tests
Bibliography

Bibliography

Recommended Core 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

Recommended Additional Bibliography

  • Chen, S.-H. (2018). Big Data in Computational Social Science and Humanities. Cham, Switzerland: Springer. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1944799
  • Eric Silverman. (2018). Methodological Investigations in Agent-Based Modelling: With Applications for the Social Sciences. Web server without geographic relation, Web server without geographic relation (org): Springer. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsbas&AN=edsbas.36B944A9