This course introduces the main issues related to the analysis of large amounts of data. The course, taught in English, is composed by two modules: big data (BD) and digital methods (DM)
Lectures are in English.
Lectures will take place at the Edificio 1 of via Conservatorio, according to the following tentative schedule:
|Wednesday||8:30 - 10:30||aula 26 (DM)|
|Thursday||8:30 - 12:30||aula 26 (BD)|
|Friday||8:30 - 10:30||aula 26 (DM)|
Any change to the schedule will be announced in class and published in paragraph News of this page.
By appointment (via e-mail).
It is possible contact the teacher by e-mail, taking care to read in advance the guide prepared by Prof. Sebastiano Vigna and clearly specifying in the message the course name and the academic year. In particular, students are encouraged to always use their academic address (i.e. based on the domain
studenti.unimi.it) signing with name and student ID number and recalling that the response time may vary depending on the teacher commitments.
The BD module is based on the following textbooks: Viktor Mayer-Schönberger and Kenneth Cukier, Big data – A revolution that will transform how we live, work, and think, Aemon Dolan, 2013 (ISBN:978-0-544-00269-2), e Bernard Marr, Big data: Using SMART Big Data, Analytics and Metrics To Make Better Decisions and Improve Performance, Wiley, 2015 (ISBN:978-1-118-96583-2)
The DM module is based on the following material: Rogers, R. 2013. Digital Methods, Cambridge, MIT Press; Hine, C. 2015. Ethnography for the Internet: Embedded, Embodied and Everyday, London Bloomsbury; additional material provided in class. It is strongly recommended to attend class using a laptop, to learn the basics of the Digital Methods Initiative tools package, and to download the free software Gephi. Students not attending class are also asked to study on the book Kozinets, RV 2010. Netnography: Doing Ethnographic Research Online. Los Angeles: Sage.
BD module: overview of the «big data» world. Analysis of the «big data» phenomenon; analyzing big masses of data; data science: an example; working with incoherent data; looking for correlation among data; datafication; the value in data; risks linked to the «big data» phenomenon; possible evolution of the «big data» phenomenon. DM module: big data (opportunities and constrains); digital methods; ethnography of the Internet; netnography; digital ethnography; etnomining and short-term ethnography; useful heuristics; data collection tools; coding/programming scrapers; sentiment analysis; content analysis; quali-quantitative text analysis; online network analysis; introduction to Gephi; digital identity analysis; twitter analysis; data visualization; research design.
The exam consists either in: i) an oral test on the content of the BD and DM modules, ii) a project per module, or iii) a project combining topics from both modules.