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Module Description

Intro | Topics | Prerequisites | Aims | Structure and teaching style

Introduction: What is this module about?

Empirical sciences rely on data. Among them, social and political sciences are no exception. Whether explicitly or implicitly, they need to be substantiated by rigorous investigations on social attitudes, actions, opinions or values. In this course, we will focus on a fast growing yet often under-examined source of data: the internet. A wider and wider part of social and political life is now based, mediated or at least related to some kind of online content. Most social settings, whether domestic or professional, in relation with governmental or charity organisations, have their online counterpart. One can less and less make business, entertain oneself, perform art, manage a church, mobilise protest, lead an electoral campaign or implement a public policy without being present and active online. All this seems to expand and diversify the capacities of social sciences to document and understand the world.

Yet, behind the unique opportunity of this ever-growing flow of data, one has to examine its relevance and quality. Where does this or that piece of information come from? Who provides it and for what explicit and implicit purposes? Is it good for sound scientific research? Last but not least, once it has been collected, do we have the tools required to treat it and confront it to theory?

Fortunately, the social and political sciences already have two long traditions of data collection. One is the art of collecting information of any kind in a systematic, reliable and valid way. The other one is to survey individuals or organisations, or to design other kinds of experiments that generate specific data. A third approach is emerging: collecting data made available by extra-academic organisations, such as search engines or administrative "open data". In all three cases, some classical methods may be adapted to online fields of investigation, before the usual series of data analyses techniques can be applied to them.

The sequence of topics in brief

  • Internet as a challenge for the Social Sciences
  • Search engines and other online tools
  • Secondary analysis of (un)official statistics
  • Questionnaire design and implementation
  • Survey data and experimental data
  • Sample design
  • 'Big data', administrative data and social media data
  • Networks and mapping
  • Basic algorithms for data exploration

Module prerequisites

No specific skills or knowledge are required, except your curiosity for data and their online development.
Students attending courses QS101 or QS103 will find some links with the present courses (QS102), but these three modules are fully autonomous and success on one does not depend on attendance on the others.

Module aims and objectives

We will review the available, classical methods of data collection in the social and political sciences, and their adaptations to fit online data. We will analyse the advantages and disadvantages of online data collection techniques, in relation to a series of concrete research questions. Throughout, we will review the benefits of online primary and secondary data for social research, as well as, conversely, make use of sociological and political theories to assess online data opportunities. In other words, the internet will be seen from three angles: as a wide source of information, as a powerful tool for investigation and as an object of cautious scrutiny.

Module structure & teaching style

The course will run on a weekly 3-hour pattern. It will be comprise lectures, discussions about assigned readings, presentations by students and hands-on activities. Students will be invited to develop their critical skills and at the same time to acquire the technical know-how necessary for rigorous online investigations. The final assessment will be individual, yet, students will be invited to perform some of the exercises in teams of two (not more).