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OBME 2130 - Digital Methods for Social Sciences

Type d'enseignement : Seminar

Semester : Spring 2018-2019

Number of hours : 24

Language of tuition : English


This course does not require any prior skill or knowledge in coding or statistics

Course Description

The main ambition of this course is to teach students how to collect and analyze data collected on the web. The focus will also be put on the design of an original research project making use of quantitative analysis of online empirical data. Classes will alternate theoretical discussions around recent scientific papers (case studies or methodological articles) with more practical training. Please note that methodology taught during the class will mainly focus on the questions of language use. Beyond readings, students will also have to produce an original empirical analysis of a web corpus (online comments, tweets, reviews, Facebook comments, etc.): design of a research question and empirical protocol, online data collection, visualization strategy, etc. This collective project will offer the opportunity to students to practice and apply the research methodologies introduced during the semester. The first session will introduce the challenges of data analytics in web studies at large. It will be followed by 8 sessions that will focus on specific methodological aspects (corpus collection, textual coding, network analysis, topic detection, etc.). The three last sessions will be centered around the collective projects of students. The class aims at bringing both technical skills and theoretical knowledge to students.


COINTET, Jean-Philippe (Associate professor)

Pedagogical format

The pedagogical format is strongly oriented toward a workshop-style class. Typically, a short theoretical talk will be given to introduce each course topic to start with. A discussion of the reading will follow before the class turns into applied mode where students will practice data analysis by themselves. It is required that students bring their laptop, no special software is required except maybe having a recent browser running.

Course validation

The final collective project will contribute to two third of the final grading. One or probably two individual take-home papers will also be assessed to complement this evaluation.


The workload should be limited to two (max three) hours a week. Students will be required to read a paper every week or to make some progress about their collective project

Required reading

  • Barberá, Pablo, et al. "Tweeting from left to right: Is online political communication more than an echo chamber?." Psychological science 26.10 (2015): 1531-1542.
  • McFarland, D. A., Lewis, K., Goldberg, A., Sep. 2015. Sociology in the Era of Big Data : The Ascent of Forensic Social Science. The American Sociologist.
  • Boyd, Danah, and Kate Crawford. "Six provocations for big data." A decade in internet time: Symposium on the dynamics of the internet and society. Vol. 21 Oxford: Oxford Internet Institute, 2011
  • Bail, C.A., Merhout, F. and Ding, P., 2018. Using Internet search data to examine the relationship between anti-Muslim and pro-ISIS sentiment in US counties. Science advances, 4(6), p.eaao5948.
  • Bakshy, Eytan, Solomon Messing, and Lada A. Adamic. "Exposure to ideologically diverse news and opinion on Facebook." Science 348.6239 (2015): 1130-1132.