85008 - Big Data For The Social Sciences

Academic Year 2020/2021

  • Docente: Oltion Preka
  • Credits: 8
  • SSD: SPS/04
  • Language: Italian
  • Moduli: Oltion Preka (Modulo 1) Enzo Loner (Modulo 2)
  • Teaching Mode: Traditional lectures (Modulo 1) Traditional lectures (Modulo 2)
  • Campus: Bologna
  • Corso: Second cycle degree programme (LM) in Public and Corporate Communication (cod. 8840)

    Also valid for Second cycle degree programme (LM) in International Relations (cod. 9084)

Learning outcomes

By the end of the course, studemts will be alble to: 1) Understand the foundations of big data, including it’s foundations in computing technology and statistics. 2) Understand the social implications of increased knowledge, surveillance, and behavioral prediction made possible by big data, and the ethical tradeoffs faced. 3) Demonstrate the ability to formulate specific study questions concerning cybersth use of big datay. 4) Understand accepted tools and practices concerning the use of the internet for social purposes. 5) Demonstrate the ability to communicate complex concepts to multidisciplinary teams including students from computing and international affairs backgrounds. 6) Be familiar with text mining techniques.

Course contents

By the end of the course, students will be able to: 1) Understand the foundations of Big Data, including its foundations in computing technology and statistics. 2) Understand the social implications of increased knowledge, surveillance, and behavioral prediction made possible by big data, and the ethical trade-offs faced. 3) Understand accepted tools and practices concerning the use of the internet for social purposes. 4) Demonstrate the ability to communicate complex concepts to multidisciplinary teams including students from computing and international affairs backgrounds. 5) Be familiar with text mining techniques.

Readings/Bibliography

These are required readings for the class:

  • Mueller, John Paul (2014) Beginning programming with Python for Dummies, eBook available free for all students here link [http://sol.unibo.it/SebinaOpac/query/python%20for%20dummies?context=catalogo]
  • Hanneman, R. A. & Riddle M. (2005) Introduction to Social Network Methods. Riverside, CA: University of California, Riverside (chapters 1,2,3,5,6,7,10,11). Available (free) online here: http://faculty.ucr.edu/~hanneman/

For those who are not familiar with Big Data in general (very easy reading):

  • Mayer-Schonberger V. & Cukier C. (2014) Big Data: A Revolution that will transform how we live, work and think, Eamon Dolan/Mariner Books.

In addition, students will be using class notes.

Teaching methods

Theoretical lectures, in-class coding exercises and homework. 

Assessment methods

Students will be required to write a short paper on a topic they are really interested in (for a two-person team). During the last two sessions of the course, students can discuss their research idea with the instructor and colleagues. The final product (paper) should be submitted two weeks after the end of the class.

Teaching tools

  • Python programming language (ANACONDA distribution)
  • Jupyter Notebook
  • Pandas
  • Matplotlib
  • NLTK

Office hours

See the website of Oltion Preka

See the website of Enzo Loner

SDGs

Quality education Gender equality Decent work and economic growth

This teaching activity contributes to the achievement of the Sustainable Development Goals of the UN 2030 Agenda.