Social Media as Data
Instructor Information
Dr. Jose Marichal (He/Him)
Email: marichal@callutheran.edu
Office Hours: By appointment via Zoom (preferred after class Wed 12pm)
Course Description
In this course, students will learn the different ways in which you can analyze social media text. Students will learn the VERY basic elements of the Python programming language, how to set up an integrated developer environment (IDE), how to find source code, how to work with Application Programming Interfaces (API) to access data, how to prepare text data for analysis and finally how to analyze and present that data using social network analysis (SNA) and natural language processing (NLP).
Course Format
This course is entirely online. There are weekly live chats using Zoom (synchronous online class meetings). The rest of your learning time will be spent watching pre-recorded video lectures and doing other assignments related to the content of the course.
Course Goals
Through completing this course, the student will be able to:
- Have a VERY basic understanding of variables, lists, operations, functions and data frames in Python.
- Understand how to work in the Jupyter notebook IDE, how to download packages in Anaconda, find source code.
- How to interact with a social media platform’s API to extract data.
- How to prepare text data.
- How to analyze and visually present that data.
Requirements & Technology
Computer: Windows 10 or Mac OS X, 3.0 GHz+ processor, 4 GB+ RAM.
Tools: Python, Anaconda, Zoom, Blackboard.
Internet: Reliable connection (rec. 50 Mbps) for Zoom and tools.
Grading (100 Points Total)
- Datacamp Python Course Modules (50 points): Completion of learning modules on CodeAcademy/Datacamp.
- Weekly Mini-Assignments (50 points): Two mini-assignments per week reflecting competencies in accessing, preparing, and analyzing data.
(Pre-Recorded Tutorials and Zoom Meetings are required components but not directly graded.)
Course Schedule
- Watch: Video Tutorials 1 & 2
- Do: Mini-assignment 1: Intro to Data Science and NLP
- Do: Week 1 Data Camp Python module
- Watch: Video Tutorials 3 & 4
- Do: Mini-assignment 2 & 3: Concepts in network analysis and NLP
- Do: Week 2 Data Camp Python modules
- Watch: Video Tutorials 5 & 6
- Do: Mini-assignment 4 & 5: Creating a dev environment and accessing data
- Do: Week 3 Data Camp Python module
- Watch: Video Tutorial 7
- Do: Mini-assignment 6 & 7: Social Network Analysis and Pre-processing/tokenizing data
- Do: Week 4 Data Camp Python module
- Watch: Video Tutorials 8 & 9
- Do: Mini-assignment 8 & 9: NLP analysis strategies
- Do: Week 5 Data Camp Python module
- Watch: Video Tutorial 10
- Do: Mini-assignment 10: Visualizing data (Seaborn and Plotly)
Policies
- Attendance: Be reflective and honest with yourself about what you need as a learner.
- Late Work: Please communicate early. Late work without prior communication may be subject to a 50% reduction.
- Academic Honesty: Standard university policies apply. Plagiarism and unethical computer use will result in sanctions.
- Netiquette: Be respectful, appropriate, and mindful of others in online communication.