Computational Social and Political Science

Throughout the Programme, students receive extensive, integrated, and cutting-edge training in analytic methods, statistics, and computational science. Students are equipped with solid methodological foundations by means of a compact training on different designs for social research and policy analysis and evaluation. The focus is on survey, experimental, and computational approaches, and will be supported by appropriate foundations in computer programming and data management, including related ethical and legal issues. Course topics include state-of-the-art techniques in multivariate analysis, machine learning, text-as-data, social network analysis and network science, causal inference, and agent-based computer simulation models. Epistemological frameworks, disciplinary theories and qualitative insights and data from the field are incorporated as the context supporting an informed use of each modelling technique.
The courses include a substantial amount of practical training, as well as individual and group project activities, closely connected with real-world data and case studies. The teaching methods aim to foster the methodological posture of computational social and political scientists, enabling students to approach the analysis of political and social phenomena starting from the formulation of relevant, empirically testable hypotheses, linking phenomena to models, designing consistent procedures for data collection and evidence mapping, and evaluating the implications of results in terms of strategic political decisions, intervention and evaluation.
The Programme requires the attainment of 84 credits from compulsory exams, including 27 credits from courses on observational and experimental designs for computational political and social research, 6 credits in computer science methods for large language models, 6 credits on ethical and legal issues related to data and computational analyses, and 45 credits on computational and statistical models for survey, digital, network, and text data. In addition, students acquire 12 credits from other additional elective and optional activities, 9 credits from internships (6 for students who need to earn 3 ECTS for Italian language A2), and 15 credits for the final thesis are provided.
Profile: Computational Social Scientist
Functions: (1) design and implement data collection on social phenomena (both offline and online); (2) analyse these data (or supervise and coordinate their analysis); (3) interpret and synthesize the results of these analyses to describe complex social phenomena, map behavioral, attitudinal, or market trends, test theories about the causes of these phenomena and trends, and provide probabilistic forecasts; (4) present the results of these activities, along with the information and insights derived from them, in textual, graphical, or audiovisual formats for public or private stakeholders.
Skills: knowledge of theories and methods for quantitative research; ability to collect and critically review relevant scientific literature; proficiency in designing research and studies, including research on groups, communities, and populations, surveys, experiments, and computer simulations; data collection skills for various types of data (numerical and textual) from online and offline sources; expertise in statistical and computational analysis of data on complex social contexts using languages such as R and Python.
Outlets: companies or organizations in the private sector (e.g., social media, human resources, corporate consulting); market research agencies; local or national public administrations and government agencies; university research institutes, public or private research centers; organizations in the non-profit sector.
Profile: Computational Analyst for Public Policy
Functions: design and implement systematic collections of evidence and data on political phenomena, including electoral campaigns and trends, the emergence and evolution of political movements and parties, and public opinion trends; analyse these data (or supervise and coordinate their analysis); interpret and synthesise results to describe complex political phenomena, map political and electoral trends, test theories about the causes of these phenomena and trends, or predict how such phenomena may unfold in the future.
Skills: knowledge of theories and methods of quantitative research; ability to gather and critically review relevant scientific literature; proficiency in designing research and studies, including experimental designs, randomized controlled trials, and the analysis of texts and documentary materials using quantitative and computational techniques with languages such as R and Python; expertise in predictive electoral models, political strategy analysis, campaign design, online disinformation tracking, and analysis; statistical and computational analysis of data on complex political contexts.
Outlets: companies or organizations in the private sector (e.g., political consulting, public opinion polling, social media), local or national public administrations or government agencies, political parties and organizations, foundations and think tanks, policy evaluation agencies, non-governmental organizations, international agencies, university research institutes, public or private research centers, or non-profit organizations.
1. Curricular requirements
Candidates for admission to the Programme may have different Bachelor's degrees, but they must have obtained at least 30 ECTS in computer science, mathematics, applied physics, statistics or econometrics (scientific disciplinary sectors: from MAT-01 to MAT-09, INF-01, ING-INF/05; from SECS-S/01 to SECS-S/06; SECS-P/05) and/or in the area of political science and sociology (scientific disciplinary sectors: SPS/04 and from SPS/07 to SPS/12), with a minimum requirements of 12 credits in the area of political science and sociology (scientific disciplinary sectors: SPS/04 and from SPS/07 to SPS/12) and at least 9 in the area of statistics (scientific disciplinary sectors: from SECS-S/01 to SECS-S/06; SECS-P/05).
Students who do not meet the requirement of 12 credits in the area of political science and sociology will be offered 4 online MOOCs (3 credits each one) in the area of political science and sociology available at the University's Digital Education Hub with a compulsory online exam to be taken online in front of a committee appointed by the Degree Program before enrolment.
2. Proficiency in English
Proficiency in English at a B2 level or higher per the Common European Framework of Reference for Languages (CEFR) is required for admission.
The B2-level requirement will be ascertained by the University Language Centre (SLAM) upon admission as follows:
- Language certificate of B2 or higher level issued no more than three years before the date of admission application. You will find the list of language certificates recognized by the University at: https://www.unimi.it/en/node/39322. The certificate must be uploaded when submitting the online application;
- English level achieved during a University of Milan degree programme and certified by the University Language Centre (SLAM) no more than four years before the date of admission application, including levels based on language certificates submitted by the applicant during their Bachelor's degree at the University of Milan. In this case the process is automatic, the applicant does not have to attach any certificates to the application;
- Entry test administrated by the University Language Centre (SLAM) according to the calendar published on the website: (https://www.unimi.it/en/node/39267/)
All those who fail to submit a valid certificate or do not meet the required proficiency level will be instructed during the admission procedure to take the Entry test.
Applicants who do not take or pass the Entry test will be required to obtain a language proficiency certificate recognized by the University (see https://www.unimi.it/en/node/39322) and deliver it to the SLAM via the InformaStudenti service by the deadline fixed for the masters programme (https://www.unimi.it/en/node/39267/).
Applicants who do not meet the requirement by said deadline will not be admitted to the master's degree programme and may not sit any further tests.
3. Personal competences and skills: assessment criteria
Admission is conditional and depends on the assessment of the personal competences and skills of the student provided by the Admission Board, whose members are appointed by the Faculty Board (Collegio Didattico).
The assessment of personal competences and skills for admission to the Programme is conducted through an online written test in English about basic competences in statistics, sociology and political science. Detailed information on the content and structure of the test content will be published on the Admission notice and on the Programme's website before the start of admissions. Candidates who do not achieve the minimum score required by the Admission Board on this test will not be admitted to the programme. The test can only be taken once.
The Admission Board will conduct an online video interview with non-EU candidates applying for a student VISA in order to further assess each applicant's competences and skills in relation to the Programme. A comprehensive list of potential interview topics is published on the Programme's website. Applicants with foreign qualifications must demonstrate that their academic credentials meet the basic requirements equivalent to those required of students with Italian qualifications.
Posti disponibili: 35 + 10 riservati a cittadini Extra UE
Bando di ammissione
Consulta il bando per scoprire le date e i contenuti del test e tutte le informazioni su come iscriverti.
Domanda di ammissione: dal 13/03/2025 al 26/08/2025
Domanda di immatricolazione: dal 17/09/2025 al 24/09/2025
Allegati e documenti
Attività formative | Crediti massimi | Ore totali | Lingua | Periodo | SSD |
---|---|---|---|---|---|
Advanced multivariate analysis | 6 | 40 | Inglese | Terzo trimestre | SECS-S/05 |
Data governance: ethical and legal issues | 6 | 40 | Inglese | Primo trimestre | IUS/20 |
Foundations of statistical modelling for social and political sciences | 9 | 60 | Inglese | Secondo trimestre | SECS-S/05 |
Policy design | 6 | 40 | Inglese | Terzo trimestre | SPS/04 |
Programming for social data science | 6 | 40 | Inglese | Primo trimestre | INF/01 SPS/04 |
Research design and experimental methods in the social sciences | 12 | 80 | Inglese | Primo trimestre | SPS/07 |
Survey methods for public opinion research | 9 | 60 | Inglese | Secondo trimestre | SPS/11 |
Attività formative | Crediti massimi | Ore totali | Lingua | Periodo | SSD |
---|---|---|---|---|---|
Agent-based modelling | 6 | 40 | Inglese | Periodo non definito | SPS/07 |
Causal inference in social and political science | 6 | 40 | Inglese | Periodo non definito | SPS/04 |
Social network analysis | 6 | 40 | Inglese | Periodo non definito | SPS/07 |
Text analytics and machine learning and large language models | 12 | 80 | Inglese | Periodo non definito | INF/01 SPS/04 |
Final exam | 15 | 0 | Inglese | Periodo non definito | NN |
Attività formative | Crediti massimi | Ore totali | Lingua | Periodo | SSD |
---|---|---|---|---|---|
Additional language skills: italian (3 ECTS) | 3 | 0 | Italiano | Periodo non definito | NN |
- Referente del CdS:Prof. Flaminio Squazzoni
[email protected] - Segreteria Studenti
Via S. Sofia 9/1 - 20122 Milano (MI)
https://www.unimi.it/it/studiare/servizi-gli-studenti/segreterie-informastudenti
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