About Me

Introductions

Dad Joke

• Why did the nearsighted man fall in the well?

• He couldn’t see that well!

Programming provides exciting opportunities for social scientists

• Digital data is exploding and programming is required to do research at scale
• Algorithms mediate more and more interactions and understanding programming can help us to analyze them
• Computational methods let us do new things
  • Natural language processing
  • Simulation
  • Large-scale experiments
• There is value in “thinking like a computer”

Goals

• Learn basic programming
• Collect data using APIs
• Perform basic visualizations using Pandas
• Learn about fundamental computational social science techniques
• Read and evaluate computational social science research
• Meaningfully progress a research project that uses computation

This is an intense class intended to teach the basics of skills used by computational social scientists

• But we can do it!
• Module 1: Python for Everybody
• Module 2: Pandas, visualizations, and APIs
• Module 3: Data cleaning, version control, etc.
• Module 4: Work on final project

Day-to-day

• Lecture
  • Recorded lecture on coding topic
  • Notebook to follow along - download and run each day
  • Class time focused on confusions + Coding Challenges
• Coding Challenges
  • Random “cold calling” for reviewing solutions
• Example paper
  • One person will present each Thursday + lead discussion
  • Others will be prepared to discuss
• Co-working

Readings

• Getting kind of stale
  • Help me find new things to read!
• Sign up to present on Google Spreadsheet (up to 2 people)
  • Present the work as though you were the researcher
  • Everyone else will skim and be prepared to ask questions

Coding Challenges

• Exercises from the book
• Jupyter Notebooks
• Suggested approach:
  • Work with a partner
  • Turn on Github Copilot
    • Make sure you understand the result!
  • Ask questions on Element
  • Look up solutions (where available)

Coding Challenge Reviews

• The coldcaller will choose someone to share in class
• Rotation for who is assigned to submit / curate solution on Element

Final Project

• Default option
  • Jupyter notebook
  • Short intro + Methods + Result section of paper
• Replication
• Do what is best for your future goals

Project Milestones

• Final project
  • Identify a dataset and general plan (September 6)
  • Project planning doc (October 18)
  • Project presentation + report (December 6 and 8)

Grades

• Goal is learning
• Two self-assessment reflections

Wiki

• Schedule
• Links to readings
• Slides and videos may be from older versions of the class
  • I will try to stay 1-2 weeks ahead

Brightspace

• Readings
• Example Projects
• Announcements

Element

• Post questions and help each other
• Post solutions to homework problems

Anaconda / VSCode Intro