Topics in Quantitative Sociology

Fall 2020 ENSAE

Social Patterns

The contemporary data deluge offers rich opportunities for sociologists to deploy old and new tools to study patterns of social life. We focus in particular on whether the combination of big data and statistical learning techniques help improve prediction of life outcomes. (Listen to a podcast about Salganik's experiment we study in class.)

Case-studies for reading, presentation and commentary

Exceptionally, in this session each in-class presentation will focus on two papers (instead of only one). All four papers are shorter in length and are based on the same data and participate in the same prediction challenge, which limits the overall time and effort for preparation.


  • [PRES]

  1. Filipova & al., 2019, Socius, "Humans in the Loop Incorporating Expert and Crowd-Sourced Knowledge for Predictions Using Survey Data"

  2. Crompton, 2019, Socius, "A Data-Driven Approach to the Fragile Families Challenge Prediction through Principal-Components Analysis and Random"

  • [PRES]

  1. Rigodon & al., 2019, Socius, "Winning Models for Grade Point Average, Grit, and Layoff in the Fragile Families Challenge"

  2. Davidson, 2019, Socius, "Black-Box Models and Sociological Explanations. Predicting High School Grade Point Average Using Neural Networks"

  • Commentaries: 1, 2, 3