Studying Society with Big and Digital Data

Settore scientifico disciplinare: 

SPS/07 - Sociologia Generale

Data inizio: 
Mercoledì, 2 Maggio 2018
Data fine: 
Mercoledì, 23 Maggio 2018
Ore totali: 
Ore totali docenti responsabili: 
Prova orale

Length: 20 hours, 8 sessions
Period: III term
Dates: from May 2nd to May 23rd, 2018
Location: Institute of Humanities and Social Sciences, Scuola Normale Superiore, Piazza degli Strozzi 1, 50123 Firenze
Aim of the course: This introductory course aims to provide students with an overview on the nexus between big/digital data and the study of social and political dynamics. The course leans on a conceptualization of Big Data as a complex set of cultural, political and scientific knowledge practices that challenge the traditional modes in which research questions are posed and framed, analyses are performed, as well as the ways in which results are communicated to the public and thus affect public discourse and debates. Consistently, it is articulated in 4 blocks, each dealing with a specific aspect of doing social research in and through big and digital data:
Block 1. Big and Digital Data: an Epistemological Shift for Social Sciences?: this block provides an overview of the implications of having increasingly large-scale datasets available to study social and political dynamics. This block will also discuss big/digital data not only as a tool for social research but also as an object of study in its own right.
Block 2. Datafied Research: practices, implications, and ethical considerations: this block deals with the methodological steps that underpin social and political research activities through big/digital data – from the identification of adequate digital/datafied objects, to query design, data collection, organization and analysis, and the communication of research results. Particular attention will be given to ethical considerations that should imbue the research process throughout.
Block 3. Studying political participation through big and digital data: this block focuses specifically on the issue of political participation and how to study it through big and digital data. Topics included in this block comprise social movements and collective action dynamics, public opinion, electoral campaigning and fake news.
Block 4. Social media and digital objects scraping: this block discusses the meanings, the potentials, and the limitations of different digital objects – e.g., Facebook posts, tweets, websites, images, Wikipedia pages, etc. – for social and political research. Different objects will be discussed in connection with the affordances of the different platforms from which they originate.
Class organization: Every thematic block is composed by two sessions that will take place during the week. In the first session, themes will be introduced through frontal lectures based on a list of references that will be communicated during the first meeting on May 2nd, 2018. In the second session, students will be invited to present a scientific article related to the specific theme of the block and will discuss it with colleagues (two/three publications at every session are foreseen). The list of readings will be made available after the list of subscribed students will be finalized.

  •         Wed, May 2nd 2018 (15-17.30): Block 1. Big and Digital Data: an Epistemological Shift for Social Sciences?
  •         Thur., May 3rd 2018 (15-17.30): presentations and discussion on articles
  •         Wed., May 9th 2018 2018 (15-17.30): processes and implications of datafication
  •         Fri., May 11th 2018(10-12.30): presentations and discussions
  •         Wed., May 16th 2018 (15-17.30): studying political participation
  •         Thur., May 17th 2018 (10-12.30): presentations and discussions
  •         Tue., May 22nd 2018 (15-17.30): social media and digital object scraping
  •         Wed., May 23rd 2018 (15-17.30): presentations and discussions

Course objectives: at the end of this course, students will be familiar with the main theoretical and empirical considerations of doing research with big and digital data.
Course exam: course evaluation will consist of the assessment of in class participation according to the following criteria: a) active participation during frontal lessons; b) presentation of scientific articles; c) active participation in articles’ discussions.