LIS-S 304 Social Media Data
- Prerequisites: None
- Delivery: On-Campus, Online
- Semesters offered: Spring (Check the schedule to confirm.)
Social media creates enormous troves of user data capturing behaviors, interests, and relationships. Social media thus holds significant value for research, business, and politics. This class examines the production of social media data, how industry and academics use this data, and the tools and techniques for analyzing it. This course includes 15 comprehensive modules, beginning with an introduction to social media as socio-technical systems. These systems are not simply data sources; they shape and are shaped by user practices and social structures. As we progress, we will delve into the social dynamics of data production and usage, evaluate a range of social media analytics techniques, and ultimately apply these methods to extract meaningful insights. The course is structured to go beyond providing technical skills for social media analytics and does not require any prerequisites. Students will engage in hands-on activities to learn tools and techniques while also critically examining the power dynamics inherent in the production of social media data. Assignments are designed to prompt students to contemplate the broader societal ramifications of leveraging social media insights for decision-making.
Program Learning Outcomes Supported
Instructors map their courses to specific Data Science Program Learning Outcomes (PLOs). Mapped program goals drive the design of each course and what students can expect to generally learn.
- A2: Data Literacy - Analyze the value and key role data plays in society in providing opportunities to expand knowledge, to innovate, and to influence.
- A4: Data Literacy - Assess values with respect to the use of data technologies.
- B5: Data Science - Identify, assess, and select appropriately among data analytics methods and models for solving real-world problems, weighing their advantages and disadvantages.
- C5: Information Science - Understand critical issues associated with the storage, backup, and security of data.
- D2: Data Ethics - Understand the relation between data, ethics, and society.
- D3: Data Ethics - Develop substantive arguments using ethical reasoning to suggest improvements to data-driven systems and practices.
- E1: Other Topics - Design, conduct, and write up results of research.
- Identify and weigh the social, political, ethical, and legal implications of social media data.
- Summarize emerging social media data production trends and how social media is used for data analysis.
- Analyze and evaluate techniques for obtaining and analyzing social media data.
- Employ analytical techniques for social media data to draw meaningful insights.
Profiles of Learning for Undergraduate Success (PLUS) Alignment
Instructors align their courses with the Profiles of Learning for Undergraduate Success. The profiles provide students various opportunities to deepen disciplinary understanding, participate in engaged learning, and refine what it means to be a well-rounded, well-educated person prepared for lifelong learning and success.
- P1.1 Communicator – Evaluates information
- P2.1 Problem Solver – Think critically
- P2.3 Problem Solver – Analyzes, synthesizes, and evaluates
- P3.1 Innovator – Investigates
- P3.2 Innovator – Designs and Creates
- P4.4 Community Contributor – Anticipates consequences
Module 1: Introduction to the Course
- Course basics and course navigation
- Syllabus quiz and pre-course survey
- Social media as data platform
Module 2: Social lives of Social Media Data
- Who generates, owns, and uses social media data
- What we can do with social media data
Module 3: Social media analytics techniques and tools
- Differentiate between the basic types of social media data available for analysis
- Identify possibilities and constraints of some available social media data and techniques
Module 4: Social media data for research
- Case studies of using social media analytics for academic research and policy design
Module 5: Social media data for business
- Case studies of using social media data for marketing and ads
Module 6: Assignment week
- Preparation, consultation, and submission of a paper assignment
Module 7: Peer review week
- Provide feedback and engage in discussion
Module 8: Planning social media data analysis
- Setting goals and plans for social media analytics
- Selecting tools to answer questions
Module 9: Getting social media data 1
- Evaluating and employing social media harvesting tools
Module 10: Getting social media data 2
- Organizing data for analysis
Module 11: Social media analysis 1
- Simple social media monitoring using Excel
Module 12: Social media analysis 2
- Social network analysis using R
Module 13: Drawing insights 1
- Discern what social media data can tell and cannot tell
Module 14: Drawing insights 2
- Evaluate insights and decisions drawn from social media analytics
Module 15: Assignment Week
- Preparation, consultation, and submission of final projects
Policies and Procedures
Please be aware of the following linked policies and procedures. Note that in individual courses instructors will have stipulations specific to their course.