- Docente: Chiara Binelli
- Credits: 8
- SSD: SECS-P/02
- Language: English
- Moduli: Chiara Binelli (Modulo Lez.) Chiara Binelli (Modulo Sem 1) Chiara Binelli (Modulo Sem 2) Chiara Binelli (Modulo D.Ass)
- Teaching Mode: Traditional lectures (Modulo Lez.) Traditional lectures (Modulo Sem 1) Traditional lectures (Modulo Sem 2) Traditional lectures (Modulo D.Ass)
- Campus: Bologna
- Corso: Second cycle degree programme (LM) in International Relations (cod. 9084)
Learning outcomes
At the end of the course, students will be able to understand the logic of the research process, be familiar with the big data revolution, and understand the advantages and value added of using big data for applied research in Social Sciences. The course is designed to improve students’ abilities to both identify and use scientific evidence to explore causal and predictive questions in the modern age of Data Science.
Course contents
This course introduces the emerging field that merges Data Science and Social Sciences to answer policy relevant questions. We begin with a discussion of the scientific method, the logic and basic concepts of empirical research, causal and predictive models. We then discuss how the big data revolution has shaped research in Social Sciences, and how to use Data Science to address research questions of policy relevance.
Readings/Bibliography
There is no given recommended textbook for this course. For each topic, a full list of readings is posted on the class website on “Insegnamenti Online” at iol.unibo.it. The expectation is that students will have done the assigned readings before the meetings.
Teaching methods
The course is organized over 10 weeks and discusses 5 main topics. Each topic is presented and discussed for 2 consecutive weeks using two teaching components. The first component is made by 2 lectures of 2 hours each and introduces students to the theory and core concepts of each topic. The second component is made by 2 seminars of 2 hours each. To promote an active participation to the seminars, students will be divided in 2 groups and will attend one seminar for each topic. The main goal of the seminars is to discuss how to bring the theory to the data. The seminars provide an opportunity for an active participation through presentations, discussions, and group projects. During the seminars, students will improve their understanding of the key concepts and methods introduced in the lectures by evaluating arguments in the discussions as well as by applying the concepts and methods in the analysis of existing work and in solving empirical exercises.
Assessment methods
There are 2 different exam formats, one for students that regularly attend and participate to classes and seminars, and one for students that do not regularly attend classes and seminars.
Regularly attending students
Students are “regularly attending students” if they skip a maximum of 5 classes. Regularly attending students must also attend all seminars. Participation will be regularly checked.
Exam for regularly attending students
The exam has 2 parts.
The first part consists in active participation during classes and seminars. Participation will be assessed in terms of attendance, active interaction, and group activities that will be organized during the seminars. This first part of the exam will count for 70% of the grade.
The second part consists in 2 open-ended questions based on the programme of the course and counts for the remaining 30% of the grade.
Students will have to take this second part by the final exam session scheduled for September 2022. To take the second part of the exam, students have to sign up on Almaesami. If regularly attending students do not take the second part of the exam by the abovementioned deadline, their grade achieved in the first part will be automatically cancelled and they will have to take the entire exam as non-attending students.
Exam for non-attending students
Written exam with 3 open-ended questions.
To take the exam, students have to sign up on Almaesami.
For all students
The only valid mark is the one achieved in the most recent attempt to pass the exam.
Students who pass the exam can refuse the final mark (thus requesting to re-take the exam) only once, in accordance with the university’s teaching regulations.
After having rejected a passing mark, any other subsequent passing mark will be recorded in the candidate’s transcripts.
Each student is personally responsible for his/her registration to the exam session on AlmaEsami. Registration closes 5 days before the exam. Therefore, it is not possible to sign up for the exam in the 5 days before the exam date.
Students who change their minds must withdraw their registration no later than 5 days before the exam. Withdrawal from the exam allows students to sign up for the following exam session and avoid a penalization of 3 points applied to the final grade obtained in the exam.
Withdrawal during the last 5 days before the exam is possible only in case of unexpected events (i.e. sickness, bereavement). In this case, students must send from their official account @studio.unibo.it an e-mail to @unibo.it and must provide a justification. If this procedure is not followed, a penalization of 3 points will be applied to the final grade obtained in the exam.
Teaching tools
The slides of the lectures will be provided.
Office hours
See the website of Chiara Binelli