Scope and Methods of Political Science
Instructor Information
Dr. José Marichal (he/him/his)
Professor of Political Science
Contact: marichal@callutheran.edu
Office Hours: Tuesday 10:45-12:15 / Thursday 12:15-1:45 / Or by Appointment
Office: Swenson 228
Who Am I?
I am a professor of political science at California Lutheran University. I specialize in studying the role that social media plays in restructuring political behavior and institutions. I published a book entitled Facebook Democracy (Routledge Press) which looks at the role that the popular social network played on the formation of political identity across different countries. My most recent work (with CLU colleagues Richard Neve and Brian Collins) looks at the ways in which social media platforms encourage antagonistic political discourse and how they could be regulated. In addition, I (with collaborators) am using computational social science methods on a number of projects including using machine learning to predict support or opposition to fracking on Twitter, a study of how individuals censor themselves when discussing politics on Facebook, and a project on uncovering the topic structure of Reddit comments on WallStreetBets. In 2018, I organized a mini-conference on Algorithmic Politics for the Western Political Science Association. Currently, I am working on a book that looks at the effect of the “Algorithmic Age” on political citizenship. I also write about diversity, multiculturalism and citizenship and I’m a massive US soccer fan.
Course Description
This course is an introduction to the rapidly changing field of scientific research in Political Science. As social media and algorithms become a larger and larger part of our lives, social scientists must adapt and learn the techniques of data science to answer questions in the field. As a result, this course will focus on three main areas: First, we will learn the research process by which political scientists conceptualize, count, categorize, measure, and interpret the world around them. Next, we will learn the statistical concepts that quantitative political scientists use to make claims about the world. Finally, we will begin to learn the tools of data science, namely the Python programming language and the data analysis packages that computational social scientists use. We will explore data science methods like machine learning, network analysis and natural language processing.
Learning Goals
CLU General Education Goals: Written and Oral Communication Skills, Critical Thinking, Information Literacy, Interpersonal and Teamwork Skills, Appreciation of Diversity, Quantitative Learning.
Political Science Department Goals: Critical Thinking, Information Literacy.
In this course, students are expected to:
- Employ different theoretical approaches towards questions of interest in Political Science
- Design a research proposal to answer a question of their choosing
- Understand the basics of descriptive, inferential and probability based statistics
- Understand the ways in which big data and data science are changing the nature of social inquiry
- Complete learning modules that teach basic Python programming and the use of data analysis packages
- Demonstrate the ability to work with other students in groups to present information
Readings and Resources
- Bhattacherjee (2012). Social Science Research: Principles, Methods, and Practices (SSR in schedule)
- Wheelan (2019). Naked Statistics (on Blackboard) (NS in schedule)
- Salganik (2017). Bit by Bit: Social Research in the Digital Age (BBB in schedule)
- DataCamp - Create a Free Account
Assignments & Assessment
Interactive Tutorials (45%): I’m using DataCamp, a site that provides online tutorials on programming and data science. Each Friday, I will ask you to complete one section of a tutorial. These tutorials will cover the basics of Python, Pandas, Matplotlib, and data science techniques. We will not meet in person on Fridays to give you time to complete modules. (15 Tutorials x 3 points = 45 points)
Midterm/Final Project (30%): Each project will focus on a question posed by Harvard professor Richard Light and his course “Reflecting on your Life.” You’ll reflect on “What does it mean to live a good life?” and collect data to determine if you are engaged in activities consistent with your values. (2 assignments x 15%)
Research Proposal & Presentation (25%): Write a research proposal including a research question, critical literature review, hypothesis, method, research design, expected results, and references. You will also present your proposal.
Grading Scale
92–100 A | 90–91 A- | 88–89 B+
82–87 B | 80–81 B- | 78–79 C+
72–77 C | 70–71 C- | 68–69 D+
62–67 D | 60–61 D- | 59 or below F
Course Schedule
Week 1: Introduction
Week 2: Epistemology / Designing Research
Week 3: Finding and Working with Data
Week 4: The Research Process
Week 5: The Role of Theory
Week 6: Research Design
Week 7: Descriptive Statistics/Visualization
Week 8: Probability
Week 9: Inference
- NS - Chapter 7: The Importance of Data