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Обычная версия сайта
Магистратура 2025/2026

Направления медиааналитики

Кто читает: Институт медиа
Когда читается: 1-й курс, 3 модуль
Охват аудитории: для своего кампуса
Язык: английский
Кредиты: 3
Контактные часы: 32

Course Syllabus

Abstract

The course aims to equip students with advanced skills in analyzing media content and its impact across various platforms. It delves into emerging trends in media analytics, including big data analysis, sentiment analysis, and predictive modeling. Students will learn to use analytical tools for measuring audience engagement, tracking media influence, and identifying key performance indicators. The curriculum emphasizes practical application of theoretical frameworks to real-world scenarios, preparing graduates for careers in research, marketing, and strategic communications within the media industry.
Learning Objectives

Learning Objectives

  • To acquaint students with the theoretical basics of media analytics
  • To overview tools for calculating and interpreting key metrics of social media analysis
  • To analyse cases of using media analytics in different areas
  • To learn principles for making reports based on collected data
Expected Learning Outcomes

Expected Learning Outcomes

  • Uses tools for social media analytics for making reports and creating dashboards
  • Assesses possible implications of data from open sources
  • Presents cases of using media analytics tools in different spheres
  • Understands possibilities and limitations of current instruments in media analytics (Big Data, AI etc.)
  • Interprets data analysis results and concludes how to use them making recommendations.
Course Contents

Course Contents

  • Foundations of Media Analytics: Key Concepts and Evolution of Approaches
  • Measuring Audience Engagement: Metrics and Tools
  • Media Impact Tracking: from Reach to Reputation Effects
  • Big Data in and AI Media Analytics: Ways of Application
  • Sentiment Analysis: Overview of Methods and Applications
  • Predictive Modeling in Media: from Data to Forecasts
  • Applied Media Analytics: from Data to Decisions
  • Presentations of Final Projects
Assessment Elements

Assessment Elements

  • non-blocking Participation in seminar activities
  • non-blocking Individual written task
  • non-blocking Individual presentation of an article
  • non-blocking Group project
Interim Assessment

Interim Assessment

  • 2025/2026 3rd module
    0.29 * Individual written task + 0.1 * Participation in seminar activities + 0.4 * Group project + 0.21 * Individual presentation of an article
Bibliography

Bibliography

Recommended Core Bibliography

  • Social media analytics : effective tools for building, interpreting, and using metrics, Sponder, M., 2012

Recommended Additional Bibliography

  • Lev Manovich. (2016). The Science of Culture? Social Computing, Digital Humanities and Cultural Analytics. Journal of Cultural Analytics. https://doi.org/10.31235/osf.io/b2y79