85008 - BIG DATA FOR THE SOCIAL SCIENCES

Anno Accademico 2020/2021

  • Docente: Oltion Preka
  • Crediti formativi: 8
  • SSD: SPS/04
  • Lingua di insegnamento: Italiano
  • Moduli: Oltion Preka (Modulo 1) Enzo Loner (Modulo 2)
  • Modalità didattica: Convenzionale - Lezioni in presenza (Modulo 1) Convenzionale - Lezioni in presenza (Modulo 2)
  • Campus: Bologna
  • Corso: Laurea Magistrale in Comunicazione pubblica e d'impresa (cod. 8840)

    Valido anche per Laurea Magistrale in International relations (cod. 9084)

Conoscenze e abilità da conseguire

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.

Contenuti

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.

Testi/Bibliografia

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.

Strumenti a supporto della didattica

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

Orario di ricevimento

Consulta il sito web di Oltion Preka

Consulta il sito web di Enzo Loner

SDGs

Istruzione di qualità Parità di genere Lavoro dignitoso e crescita economica

L'insegnamento contribuisce al perseguimento degli Obiettivi di Sviluppo Sostenibile dell'Agenda 2030 dell'ONU.