93560 - Information and Big Data (Lm)

Course contents

The course will focus on the topic of data analysis, data visualization and interpretation of data and polling in media and public debate.

A specific focus will be placed on the relationship between data and perceptions and on misleading uses of data by media and public personalities.

We will explore methods and principles of data interpretation and visualization and we will examine case studies drawn from politics and elections, economy and society, health.

The course will be split into these segments:

• Power of data and effects on perceptions and public debate
• Data visualization 1: charts. Principles, tools, types of charts, examples of misleading charts
• Data visualizations 2: maps. Principles, tools, types of charts, examples of misleading maps
• Polls and their interpretation in public and political debate
• Data journalism
• Good practices in dataviz

The course will contain several practical group works and simulations on data interpretation and presentation.

Readings/Bibliography

Study of the slides and additional materials (presentations, scientific papers, media articles) required.

Compulsory reading of at least one of the following books (others are recommended) for attending students. For students not attending classes, compulsory reading of at least 3 of the following books.

Carl T. Bergstrom, Jevin D. West, Calling Bullshit: The Art of Skepticism in a Data-Driven World

Sanne Blauw, Il più grande bestseller di tutti i tempi (con questo titolo). Come difendersi da chi ci inganna con i numeri

Alberto Cairo, Come i grafici mentono, Raffaello Cortina Editore

Alberto Cairo, L'arte funzionale. Infografica e visualizzazione delle informazioni

Alberto Cairo, L' arte del vero. Dati, grafici e mappe per la comunicazione

Sally Caldwell, Statistics Unplugged

Darrell Huff, How to Lie with Statistics

Mark Monmonier, How to Lie with Maps

Nando Pagnoncelli, Dare i numeri. Le percezioni sbagliate sulla realtà sociale

Charles Wheelan, Naked Statistics

Teaching methods

Due to the restrictions imposed by the current health emergency, teaching will be carried out with traditional methods: the professor will always be in the designated classroom, students will alternate in attendance according to a schedule of shifts being defined (more detailed information on the shifts and how to access the face-to-face lesson will be provided later). It will always be possible to connect remotely and follow live lessons via the Teams platform.

Traditional lessons supported by slides, audiovisual and digital materials, shared with students. Group workshops and simulations will also be part of the course. There might be presentations and talks by experts in the media, polling & data analysis sector.

ATTENTION: Given the fluidity of the emergency situation and since this program is published in July 2020, the teaching methods may change in the coming months. In this case, timely communication will be given through an update of this program, as through appropriate notices published on the institutional channels, i.e. on the professor’s page, on the INCOM website and on the official INCOM Facebook page. All students are encouraged to consult these resources periodically.

Assessment methods

The class will be split into small groups and each group will prepare a data visualization project based on a dataset. The project will be presented, analyzed and discussed with the students and the professor in the final period of the course. Each student will also have to answer oral questions on the book chosen.

Students not attending classes: you will be required to prepare and submit a data visualization project based on a dataset + oral exam concerning the 3 books selected from the list above.

Teaching tools

Presentations, audiovisual material, videos, links and online resources, possibly meetings with experts and professionals.

Office hours

See the website of Lorenzo Pregliasco