Universidade Nova de Lisboa

Universidade Nova de Lisboa

NOVA Information Management School

Social Media Intelligence

Code

400028

Academic unit

NOVA Information Management School

Credits

7.5

Teacher in charge

Teaching language

Portuguese. If there are Erasmus students, classes will be taught in English

Objectives

Social media analytics is the methodology of gathering data from vast amounts of semi-structured and unstructured social media data to extract insights that help to make better business decisions.
The course offers concepts, tools, tutorials, and case studies to extract and analyse social media data.
The course objectives are:
. Understand different types of social media and social media analytics.
. Understand text analytics and sentiment analysis concepts, techniques, and tools.
. Understand social media networks concepts, techniques, and tools
. Understand social media location analytics concepts, techniques, and tools
. Understand social media risks and privacy and ethical considerations

Prerequisites

 

Subject matter

1. Introduction to social media
2. Social media analytics: an overview
3. Social media text analytics and sentiment analysis
4. Social media networks analytics
5. Social Media Location Analytics
6. Managing Social Media Risks
7. Privacy and ethical considerations

Bibliography

Social Media Metrics for Dummies, Leslie Poston; Social Media Metrics How to Measure and Optimize Your Marketing Investment, Jim Sterne; Stand Out Social Marketing: How to Rise Above the Noise, Differentiate Your Brand, and Build an Outstanding Online Presence, Mike Lewis; 0; 0

Teaching method

The unit is based on a mix of theoretical lectures and practical lectures and tutorials. The theoretical sessions include the presentation of theoretical concepts and methodologies and resolution by the teacher of application examples.
The main objective of the practical classes is to familiarize students with the software to perform the analysis and data explorations tasks.

Evaluation method

Assessment:
1st term - Exam (60%), Project (40%)
2nd term - Exam (60%), Project (40%)

Courses