Social Media Analytics

This course presents and teaches analytic methods that can be used to understand social and business insights. Students will be exposed to both the benefits and limitations of relying on social media data compared to statistical social research methods. The course teaches the foundational skills of social media listening including the creation of common social media metrics and shows how social media data can be used to provide insights into social processes of consumer society and markets.

• to provide theoretical knowledge and practical skills on contemporary social media analytics and its application to solving social and business problems; • to develop the capacity to collect social media data and to apply theoretical methods of social network analysis to social media data; • develop knowledge and skills in visualizing social media data and presenting results.

Basic knowledge of mathematics and programming.

1. Social media data and key performance indicators. 2. network characteristics. Data transformations. Sociometry. 3. Testing of social media data hypothesis. 4. Cluster analysis for raising hypothesis. 5. Visualisation and analysis of complex media data. 6. Virtual communities. 7. Machine learning for social media data analysis.

1. Depth of knowledge of the presented material 2. Ability to use scholar knowledge in a development of new assignment 3. Ability to find, analyze and use additional scholar resources (articles) 4. Practical demonstration of social media analytics knowledge and practical skills for working with social data. 5. Meaningfully explanation of the application of SNA solution. 6. Presentation of project results to other students and the lecturer, group discussions.