Big Data and Digital Methods
A.Y. 2019/2020
Learning objectives
The course aims to provide students with the theoretical and methodological tools needed to autonomously conduct qualitative and quantitative empirical research based on digital data. Big Data and digital methods will, on the one hand, be problematized through theoretical reflections on the datafication of contemporary societies; on the other hand, they will be introduced as central methodological approaches in today's social and marketing research. During the course each aspect of the digital inquiry will be covered step by step: research design, data collection and cleaning, analysis, interpretation and visualization of the results. Students will be guided through a hands-on approach to the use of different techniques (digital ethnography, network analysis, qualitative and quantitative text analysis) and analysis tools, also thanks to intensive exercise sessions. This training course will end with the realization and presentation by students of digital surveys on research topics introduced in class.
Expected learning outcomes
Students are expected to become competent in crafting original research on digital platforms. Three main skill sets sould be mastered by students: 1) theoretical competence, 2) methodological competence, 3) technical competence. For the first skillset students should be familiar with current theoretical expertise on digital platforms, including digital methods based approaches as well as politcal economy ones. For the second skill set students are expected to become proficient with an array of different research methods, such as: quantitative analysis (eg sentiment analysis, influencer detection), ethnographic analysis, network analysis. It is expected that students will be more familiar with one specific aspect but working knowledge of all will be required. For the third skill set students are expected to became proficient in the technical tools needed to finalize research for digital platforms: including data mining and data analysis for python, as well as third party data analysis tools.
Lesson period: First trimester
Assessment methods: Esame
Assessment result: voto verbalizzato in trentesimi
Single course
This course cannot be attended as a single course. Please check our list of single courses to find the ones available for enrolment.
Course syllabus and organization
Single session
Responsible
Lesson period
First trimester
Course syllabus
The course aims to provide students with the theoretical and methodological tools needed to autonomously conduct qualitative and quantitative empirical research based on digital data. Big Data and digital methods will, on the one hand, be problematized through theoretical reflections on the datafication of contemporary societies; on the other hand, they will be introduced as central methodological approaches in today's social and marketing research. During the course each aspect of the digital inquiry will be covered step by step: research design, data collection and cleaning, analysis, interpretation and visualization of the results. Students will be guided through a hands-on approach to the use of different techniques (digital ethnography, network analysis, qualitative and quantitative text analysis) and analysis tools, also thanks to intensive exercise sessions. This training course will end with the realization and presentation by students of digital surveys on research topics introduced in class.
The course is divided into two modules: 1) big data 2) digital methods.
The first module will provide students with the skills necessary to analyze a data set using the python programming language.
The second module will provide a series of theoretical and methodological skills suitable for analyzing digital phenomena, particular attention will be paid to the dynamics of digital platforms.
The course is divided into two modules: 1) big data 2) digital methods.
The first module will provide students with the skills necessary to analyze a data set using the python programming language.
The second module will provide a series of theoretical and methodological skills suitable for analyzing digital phenomena, particular attention will be paid to the dynamics of digital platforms.
Prerequisites for admission
None
Teaching methods
Lectures and lab activities. The course will be held in English.
Teaching Resources
Rogers, R. (2013). Digital methods. MIT press.
Srnicek, N. (2017). Platform capitalism. John Wiley & Sons.
Srnicek, N. (2017). Platform capitalism. John Wiley & Sons.
Assessment methods and Criteria
At the end of the course, students are required to demonstrate their knowledge of the program given by submitting two contributions:
for the first module students are required to create and present digital surveys on research topics introduced in the classroom;
for the second module the presentation of a python program is required for the analysis of a database chosen by the student through dedicated libraries.
for the first module students are required to create and present digital surveys on research topics introduced in the classroom;
for the second module the presentation of a python program is required for the analysis of a database chosen by the student through dedicated libraries.
INF/01 - INFORMATICS - University credits: 6
SPS/08 - SOCIOLOGY OF CULTURE AND COMMUNICATION - University credits: 6
SPS/08 - SOCIOLOGY OF CULTURE AND COMMUNICATION - University credits: 6
Lessons: 80 hours
Professors:
Anselmi Guido, Marchi Massimo
Shifts:
-
Professors:
Anselmi Guido, Marchi MassimoProfessor(s)