Social Analytics and Applications
Description
In today’s globally connected, online and mobile world, social media platforms are fast becoming the dominant means of communication and it is revolutionizing the way businesses communicate with their customers. Many popular social media platforms such as Facebook and Twitter allow for instant, real-time multi-way communication. Collecting and analysing data from multiple online sources require an Information Technology infrastructure. The data collected from online sources create a gold mine for businesses that want to understand and predict consumer and market behaviour. By leveraging sophisticated computing technologies, big data analytics can produce actionable insights valuable to the core operations of the business. This course will explore emerging methods and applications for understanding online user behaviour on popular social media platforms. Students will be exposed to a variety of real-world business cases, a collection of data analytics tools, best practices and hands-on exercises. Students will learn how to 1) identify analytics problems, 2) use data analytics tools and identify types of analysis to be performed, and 3) close the loop (the process of taking the analysis results and interpreting it contextually).
Requisites
Prerequisites: IS200/IS111/SMT111/CS101/COR-IS1704 - Pre-req
Co-requisites: None
Anti-requisites: None
Attributes
Department: SCIS
Course Level: Undergraduate
Tracks: IS Major: Software Development Track IS/T4BS: Business Analytics Track
Areas: Advanced Business Technology Major Analytics Major Business Options Econ Major Rel/Econ Options Grad Req - Dig Tech/Data Ana (Intake 2024 onwards) IS Depth Electives IT Solution Development Electives Social Sciences/PLE Major-related Technology & Entrepreneurship
Learning Outcomes
Graduate Learning Outcomes
Disciplinary Knowledge, Critical thinking & problem solving, Innovation and enterprising skills, Collaboration and leadership, Communication, Self-directed learning
Competencies
Data Analytics, Computational Modelling, Data Engineering, Pattern Recognition Systems, Text Analytics and Processing