SOUNDS AND NOISE IN THE PERIOD OF BIG DATA
Stampa
Enrollment year
2016/2017
Academic year
2017/2018
Regulations
DM270
Academic discipline
SPS/08 (SOCIOLOGY OF CULTURE AND COMMUNICATION)
Department
DEPARTMENT OF POLITICAL AND SOCIAL SCIENCES
Course
PROFESSIONAL COMMUNICATION AND MULTIMEDIA
Curriculum
PERCORSO COMUNE
Year of study
Period
1st semester (02/10/2017 - 16/12/2017)
ECTS
6
Lesson hours
36 lesson hours
Language
Italian
Activity type
ORAL TEST
Teacher
COSTA PAOLO (titolare) - 6 ECTS
Prerequisites
No special technical skills are required, but familiarity with Microsoft Excel can help. Unexperienced students are recommended to exploit online training opportunities (e.g. Coursera, Udemy, ...) or to take advantage of the free tutorials available on YouTube.
Learning outcomes
The course is aimed at encouraging a reflection on the technical, socio-political, cultural and ethical implication of the paradigm of big data, i.e. the large aggregations of data flowing in real time from multiple sources.
Course contents
The course includes two parts: an introductory part (providing an overview of the so-called big data paradigm) and an in-depth part (focusing on its impact on the news media industry).
The introductory part (6 lessons, 12 hours in total) explores the nature of the phenomenon and its historical roots. Four major domains are considered to highlight the most significant changes driven by the big data paradigm:
- Information and journalism
- Marketing and advertising
- Finance
- Bioinformatics, medicine and pharmaceuticals
In the in-depth part (12 lessons, 24 hours in total) the following topics will be analyzed and discussed:
- How Google and Facebook algorithms are influencing the public opinion
- Fake news and misinformation channels
- Automatic news production technologies
- Practice and tool of data journalism
Teaching methods
The course is structured with front-end lectures, including breaks for discussion and group activities that requires the students to familiarize with fact checking, data scraping and data visualization tools.
Reccomended or required readings
1) Dominique Cardon, À quoi revent les algorithmes, Parigi, Seuil, 2015 (trad. it. Che cosa sognano gli algoritmi. Le nostre vite al tempo dei big data, Milano, Mondadori, 2016)
2) Eli Parisier, The Filter Bubble: What the Internet is Hiding from You, New York, Penguin, 2011 (trad. it. Il filtro. Quello che internet ci nasconde, Milano, Il Saggiatore, 2012)
3) Executive Office of the President, Big Data: Seizing Opportunities, Preserving Values, The White House, 2014
4) John Mair, Richard Lance Keebe (a cura di), Data Journalism: Mapping the Future, Bury St Edmunds, Abramis, 2014
5) Amit Datta, Michael Carl Tschantz, Anupam Datta, Automated Experiments on Ad Privacy Settings, in “Proceedings on Privacy Enhancing Technologies 2015”, 2015 (1), 92–112
6) Frank Pasquale, The Secret Algorithms That Control Money and Information, Harvard, Harvard University Press, 2015
Assessment methods
The final exam will be comprehensive and entirely oral-type
Further information
Sustainable development goals - Agenda 2030