Singapore University of Social Sciences

Social Media Metrics & Analytics (MKT365)

Synopsis

The objective of MKT365 Social Media Metrics & Analytics is to equip students with practical skills in acquiring and analysing data from social media with Python. Students will be exposed to the analytic methods that can be used to convert social media data to marketing insights. Students will be able to implement Python tools for data collection, gathering the information needed to get started with applications such as natural language processing (NLP), social network analysis, and data visualization. This course will allow students to learn how to access data from mainstream social networks such as Twitter and Facebook, and how to perform different types of analysis in order to extract useful insights from the raw data and to present the results to support decision making in digital marketing.

Level: 3
Credit Units: 5
Presentation Pattern: Every July

Topics

  • Introduction to social media and social data
  • Application Programming Interface (API)
  • Python development environment setup
  • Web scrapping in Python
  • Tokenization and frequency analysis
  • Natural language processing (NLP)
  • Social data mining in Python
  • Social media sentiment analysis
  • Social network analysis
  • Data visualization
  • Time series analysis
  • Evidence-based marketing decisions in the digital age

Learning Outcome

  • Discuss the fundamentals of extracting and processing social media content
  • Formulate social media metrics
  • Examine current methods for web scraping
  • Apply natural language processing (NLP) for unstructured data
  • Construct a strategy for textual data analysis
  • Evaluate the different methods in data visualization
  • Demonstrate proficiency in written and verbal communication skills in social media metrics and analytics
  • Develop the essential social media analytics knowledge and interpersonal skills to work effectively in a team
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