General course information

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. The size and richness of social media data therefore provides 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 the analytic 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 toolkit will equip students with the ability to independently interpret, analyse and develop social media strategy.

R and Python will be be used for the purposes of demonstrating methods. Prior knowledge od the programming language syntax is not necessery for the understanding of key concepts. However, to utilize the course content in the standalone analysis, learning some of the basic syntax is warmly recommended.

The course will touch upon several data science concepts that have become standard tools in the analysis of social media (but also have more general relevance) such as: working with databases (SQL,Google Big Querry), web data (web scraping, API), data manipulation and cleaning (tidyverse, pandas, data.table), IT ollaboration and code sharing (Git, GitHub) and open source reporting (RMarkdown).

Main aims of the course are:

  1. Catching up with the current state and trends in the social media space
  2. Understanding IT infrastructure (Big Data) of social media platforms
  3. Identification of relevant topics in social media research and business
  4. Understanding tools, methodology and results in social media analytics
  5. Application of key priniples, tools and methods for independent social media research c

The course will enable students to understand and implement advanced statistical analysis, facilitate inclusion in the modern analytical paradigm (computational social science) and cutting edge technological trends in data processing (data science). In addition to the emphasis on the academic application of the acquired knowledge, the course will make it easier for students to get involved in the business IT sector on the side of analytics as well as management.

Course Syllabus

Official course syllabus is available on English and Croatian language.
Unofficial course syllabus can be downloaded here (check for updates).

Course Literature

There is no comprehensive book on the topic of social media analysis. Furthermore, this field is rapidly changing and lerning materials depreciate quickly (mostly due to data avaliability). Therefore, the following following list of books are recommended: