Computational Methods for Social and Behavioral Scientists

Jeremy Foote

Brian Lamb School of Communication

2024-11-05

My goals

• Argue that digitization of data is one of the most important changes in social science
• Introduce some computational methods tools and examples of research using them
• Have a conversation and not just a lecture

Digital Data Revolution

• Many of the actions that people take are mediated by digital technologies
• In many cases, these actions are recorded and stored
  • Social media
  • Online communities
  • Phone calls
  • GPS locations
  • Financial transactions
  • Health records

Digital Data Revolution

• These data are often:
  • Big
  • Always-on
  • Non-reactive
  • Temporally fine-grained
  • Rich
• They allow us to study people as they act, making real decisions, at scale

Salganik, M. (2018). Bit By Bit

Computing Revolution

• The cost of storing and analyzing data has plummeted

Computing Revolution

What is Computational Social Science?

• Broadest version: using computers to help with social science research
• Could include statistical and visualization software, Qualtrics, etc.
• I’ll focus on using computational tools that enable new kinds of research

Data Science vs. Computational Social Science

• Imagine some sort of social process; we might represent it as:
  • \(\hat{Y} = \mathbf{\hat{\beta}} \mathbf{X} + \epsilon\)
• Data science (and particularly machine learning) is often interested in prediction
  • Caring about \(\hat{Y}\) rather than \(\hat{\beta}\)
• Computational social science is typically interested in explanation and understanding (correctly estimating \(\hat{\beta}\))

Data Science for Social Scientists

• Sometimes scientists are interested in prediction
  • E.g., Classifying people or texts
• Machine learning methods can also be used for:
  • Reducing dimensionality
  • Avoiding overfitting
  • Generating hypotheses

Discussion Pause

• Are there ways that machine learning is used in your field?
• Are there ways that you think it could be?

Examples of Computational Social Science

Large-scale analyses

Large-scale analyses

• Goel et al. looked at over 1 billion tweets to study how information spreads

Large-scale analyses

• Really important opportunities for studying groups, which are often expensive and difficult to study
• E.g., Our paper looking at the early-stage structures of ~1,000 wiki communities

• Not only a huge number of communities, but at early stages. Only possible because of always-on data

Social Network Analysis

• Studying outcomes in terms of relationships
• Doesn’t assume that people are independent
• Statistical methods are complex and computationally expensive

Computational Text Analysis

• Reading and analyzing texts takes a long time!
• Automated methods can quickly analyze vast amounts of text
• Inductive methods (unsupervised)
  • Topic modeling
  • Word embeddings

Computational Text Analysis

• Deductive methods (supervised)
  • Sentiment analysis
  • Named entity recognition
  • Classification

Agent-based Modeling

• Using theory, develop of model of how individuals make decisions
• Simulate what happens when many individuals interact

  

Discussion Pause

• Any questions about these methods?
• Are there ways that you think these methods could be used in your field?

Large-scale field experiments run by computers

• Facebook’s election study
  • Inivited 14.6 million users to participate
  • ~76K participants

• Our experiments on toxicity and chatbots
  • Behavior before and after participating

Citizen Science

• Pre-computers, organizing data was incredibly expensive and difficult

Citizen Science

• Today, we can organize the work of thousands of people fairly easilty
  • iNaturalist
  • Galaxy Zoo
  • Protein folding
  • SETI@home

Generative AI tools

• Lots of current research on LLMs
  • How will LLMs become part of the social world?
• LLMs as tools for social science research
  • Brainstorming partners
  • Research assistants (e.g., summarizing papers, classifying texts)
  • Editors / reviewers
  • Blurring the line betweeen method and collaborator

Discussion Pause

• Any questions about these methods?
• How are you using AI in your current research workflow?

Ethical concerns of Computational Social Science

• People are often unaware of how their data are being used, even if it is “public”
• Data can be used by bad actors
• Really important to balance privacy and research goals

Methodological concerns of Computational Social Science

• Hard to do, especially for really large-scale analyses
• Algorithmically confounded
• Data may be missing or biased in invisible ways
• Data collection processes may change over time in invisible ways
• Nonrepresentative samples

Learn More

• Salganik, M. (2018). Bit By Bit
• Take my class (Spring 2026)

Optional activity

Design a study that uses computational methods to study a question you are interested in