McCourt School - Foundations

Training Graduate Students for a Career in Computational Social Science

Prof. Tiago Ventura | McCourt School | Georgetown University

2023-08-18

Plans for today

• Introduction: Who am I and how I got here.

• Training Graduate Students for a Career in Computational Social Science (article here)

• Lots of Discussion

About me

• Professor Tiago Ventura (he/him):

  • Assistant Professor at McCourt School.
  • Before that: Postdoc at CSMAP-NYU and a Researcher at Twitter.
  • PhD from the University of Maryland, College Park
  • PhD from State University of Rio de Janeiro, Brazil

Summer Institute in Computation Social Sciences

Read more about SICSS

Computational Social Science

We define computational social science as a field that engages the social sciences and data science by applying novel digital and digitized data and computational methods to advance social scientific understanding of human behavior

Formalizing the Hidden Curriculum

• Step 1: Learning Data Science Skills

• Step 2: Build a CSS Portfolio

• Step 3: Engage in the CSS Networks

Step 1: Learning Data Science Skills

• Programming fluency in R and/or Python.

• Experience with data management, particularly with managing large, messy, and unstructured data.

• End-to-end research pipeline + Domain expertise.

• Build strong foundations in statistical inference, causal inference and machine learning.

Step 2: Building a Computational Social Science Portfolio

• Engagement with social and applied aspects of a data science.

• Learn and use Git/Github for ALL YOUR PROJECTS.

• Make your data science project available on Github and write blog posts about them

Step 3: Connecting with Computational Social Scientists

• Attend CSS conferences and focus on horizontal networking

• Internships are hugely important (All tech companies offer + non-profits, such as Civic Digital Fellowship and Data Science for Social Good Fellowship)

• Online networks: linkedin + Twitter + Github

Q&A