Social media analytics
Code: 227718
ECTS: 3.0
Lecturers in charge: izv. prof. dr. sc. Ivan Balabanić
Lecturers: dr. sc. Luka Šikić - Seminar
Take exam: Studomat
English level:

1,0,0

All teaching activities will be held in Croatian. However, foreign students in mixed groups will have the opportunity to attend additional office hours with the lecturer and teaching assistants in English to help master the course materials. Additionally, the lecturer will refer foreign students to the corresponding literature in English, as well as give them the possibility of taking the associated exams in English.
Load:

1. komponenta

Lecture typeTotal
Lectures 15
Seminar 15
* Load is given in academic hour (1 academic hour = 45 minutes)
Description:
The social media has become a powerful tool to create knowledge and propagate opinions.
Simultaneously, social media has created an unprecedented opportunity for companies to engage real-time interactions with consumers.
Furthermore, the size and richness of social media data has provided a deep reservoir of insights to understand the society and transform business and marketing operations.
The learning social media analytics course will enable students to understand social media and grasp the analytics tools to leverage social media data.
The course will describe the current state and trends in the social media space, clarify the technology infrastructure for social media platforms and show how AI, linguistic and statistical methods can be used to study relevant social media topics.
The course will introduce state of the art tools for social media analysis such as: data visualization, sentiment analysis, topic modelling, social network analysis, machine learning, natural language processing, neural networks.
This toolset will equip students with the ability to independently interpret, analyse and develop social media strategy.

Learning outcomes at the level of the programme to which the course contributes:
Interpret professional and scientific content orally and in writing.
Analyse and interpret social phenomena.
Analyse and interpret the impact of social context and social change on human development.

Expected learning outcomes at the level of the course:
1. Understand the state and contemporary trends in the social media space.
2. Understand ICT infrastructure for social media.
3. Understand and apply key concepts in social media metrics.
4. Understand specific and unique aspects of the particular social media platform.
5. Identify thematic relevance in the analysis social media analysis.
6. Interpret the results of peer-reviewed frontier social media analysis.
7. Ability to collect, clean and prepare social media data for analysis.
8. Apply state of the art methods and use adequate tools for the social media analysis.
9. Monitor consumers and competitors and glean deeper consumer insights based on advanced social media data modelling.
10. Develop social media strategy and measure social media campaign effectiveness.

Course content:
1. Course introduction and overview
2. Current state and latest trends in the social media space
3. IT prerequisites and programming language syntax (R, Python) for the social media analysis
4. Big Data infrastructure and data acquisition procedures (API, Web/Screen Scraping) for social media analysis
5. Methods for social media analysis I (descriptive statistics, visualization)
6. Methods for social media analysis II (network analysis, Natural Language Processing)
7. Methods for social media analysis III (time series, machine learning, deep learning, neural networks)
8. General principles of digital marketing (key performance indicators, search engine optimization, social media listening)
9. Twitter: trend formation and event detection
10. Facebook: analysis of the institutional, political and brand reach
11. Instagram: influencer market space and image recognition
12. LinkedIn: business network and geolocation analysis
13. Online portals and forums: text analysis and application od NLP methods
14. Traditional media (newspaper, TV, radio): public sentiment analysis and opinion polarity
15. Future trends in social media
Literature:
1. semester
SOC-dipl (4469): Izborni kolegiji - Regular studij - Sociology

2. semester
SOC-dipl (4421): Izborni kolegiji u 2. semestru (ZN i NAST smjer) - Regular smjer - Science Stream
SOC-dipl (4469): Izborni kolegiji - Regular studij - Sociology

3. semester
SOC-dipl (4469): Izborni kolegiji - Regular studij - Sociology

4. semester
SOC-dipl (4421): Izborni kolegiji u 2. semestru (ZN i NAST smjer) - Regular smjer - Science Stream
SOC-dipl (4469): Izborni kolegiji - Regular studij - Sociology
SOC-dipl (4421): Izborni kolegiji u 2. semestru (ZN i NAST smjer) - Regular smjer - Teaching Stream
Consultations schedule:
  • dr. sc. Luka Šikić:

    Thursdays from 15:00-16:00. Please send and email in advance.

    Location: 18
News

Informations

Hrvatski studiji Sveučilišta u Zagrebu pokrenuti su i ustrojeni 16. studenoga 1992., isprva samo kao dvosemestralni Sveučilišni komparativni studij hrvatske filozofije i društva. Taj je program potom preoblikovan u program redovitog četverogodišnjeg studija.

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