Computational Social and Political Science
Corso in presenza
Computational Social and Political Science
Scheda del corso
A.A. 2026/2027
Laurea magistrale
LM-62/88 R - Scienze della politica/Sociologia e ricerca sociale
The Master's Degree Programme in Computational Social and Political Science (CSPS) equips students with the knowledge and competences needed to provide empirically-grounded and theoretically-informed explanations of political and social phenomena applying computational and quantitative methods of analysis to quantitative and qualitative data. Entirely taught in English, the program combines the hypothesis-driven deductive approach typical of the social sciences with the inductive approach of data science, enabling students to develop a robust conceptual, methodological, and practical repertoire for empirically grounded analysis of social and political phenomena. Graduates are able to conduct projects in social and political research, with observational or experimental research designs, with the aim of testing theoretically-grounded hypotheses, exploring aggregate phenomena and trends, and developing evidence-based proposals for political and social interventions. Students work with primary survey data, digital data (including social media data), and secondary data, including numerical and textual data, to be collected, managed and analyzed using statistical or computational models, large language models, machine learning, and statistical learning techniques. By integrating attention to theory, qualitative data and factors, and advanced computational techniques, students are stimulated to develop a mindset for causal inference and fine-grained detection of generative, causal mechanisms driving complex socio-political outcomes, including collective opinions, social dynamics, and political trends.
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.
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.
The CSPS Programme trains the following professional profiles:
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.
Statistiche occupazionali (Almalaurea)
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.
Statistiche occupazionali (Almalaurea)
The CSPS Programme promotes internationalization among its students by encouraging their participation in the Erasmus+ Programme. Erasmus+ offers opportunities for students to engage in study exchanges, training programmes, and work experiences across various EU countries. Students can spend between three and twelve months abroad, which may include a traineeship period. Additional grants are available to support their studies or training abroad. Upon completion, students receive full recognition of their achievements in terms of credits towards their degree. Student mobility is facilitated through "inter-institutional agreements" between sending and receiving institutions, ensuring seamless transitions and academic integration. Moreover, students can opt for the traineeship program (Placement), allowing them to undertake internships abroad ranging from two to twelve months, beginning as early as the first year of study. For traineeships that are part of the curriculum, the sending institution provides full academic recognition. For non-curricular traineeships, recognition is granted through inclusion in the Diploma Supplement or a traineeship certificate for recent graduates. Traineeships may be conducted with private or public companies, including Public Administration/governmental organizations, as well as educational or research centers.
Course attendance is not required but is strongly recommended.
Immatricolazione
In order to ensure high quality education (in particular with respect to the capacity constraints necessary to run laboratories, and to hold individual and group presentations in some courses), the maximum number of students who can enroll in the Master's Degree programme in Computational Social and Political Science is set at 35, plus 10 places reserved for international non-EU candidates residing abroad. Applicants will be selected on the basis of an entrance test, according to the procedures defined in the admission notice.
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).
2. Proficiency in English
Proficiency in English at level B2 or higher according to 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:
- Valid language certificate at B2 level or higher, issued no more than three years before the application date. The list of language certificates recognized by the University is available 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 application date, including levels based on language certificates submitted by the applicant during their Bachelor?s degree at the University of Milan. Verification will be carried out automatically, no documents need to be uploaded.
- Entry test administrated by the University Language Centre (SLAM) according to the calendar published on the website: (https://www.unimi.it/en/node/39267/)
Applicants 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 submit it to SLAM via the InformaStudenti service by the deadline set by the master?s degree programme (https://www.unimi.it/en/node/39267/).
Applicants who fail to 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.
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).
2. Proficiency in English
Proficiency in English at level B2 or higher according to 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:
- Valid language certificate at B2 level or higher, issued no more than three years before the application date. The list of language certificates recognized by the University is available 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 application date, including levels based on language certificates submitted by the applicant during their Bachelor?s degree at the University of Milan. Verification will be carried out automatically, no documents need to be uploaded.
- Entry test administrated by the University Language Centre (SLAM) according to the calendar published on the website: (https://www.unimi.it/en/node/39267/)
Applicants 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 submit it to SLAM via the InformaStudenti service by the deadline set by the master?s degree programme (https://www.unimi.it/en/node/39267/).
Applicants who fail to 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 24/03/2026 al 12/06/2026
Domanda di immatricolazione: dal 02/07/2026 al 09/07/2026
Servizi online
Per approfondire:
Ammissioni A.A. 2026/2027
Sono già disponibili i bandi di ammissione per l’anno accademico 2026/27, consulta il bando per scoprire le date e i contenuti del test e tutte le informazioni su come iscriverti.
Manifesto ed elenco insegnamenti
Obbligatorio
| Attività formative | Crediti massimi | Ore totali | Lingua | Periodo | SSD |
|---|---|---|---|---|---|
| Advanced multivariate analysis | 6 | 40 | Inglese | Secondo trimestre | STAT-03/B |
| Data governance: ethical and legal issues | 6 | 40 | Inglese | Primo trimestre | GIUR-17/A |
| Foundations of statistical modelling for social and political sciences | 9 | 60 | Inglese | Primo trimestre | STAT-03/B |
| Policy design | 6 | 40 | Inglese | Terzo trimestre | GSPS-02/A |
| Programming for social data science | 6 | 40 | Inglese | Primo trimestre | GSPS-02/A INFO-01/A |
| Research design and experimental methods in the social sciences | 12 | 80 | Inglese | Secondo trimestre | GSPS-05/A |
| Survey methods for public opinion research | 9 | 60 | Inglese | Terzo trimestre | GSPS-07/A |
Attività a scelta e regole di composizione del piano didattico
1 - Students must earn 6 credits/ects for Elective substantial course
sarà attivato dall'A.A. 2027/2028
Obbligatorio
| Attività formative | Crediti massimi | Ore totali | Lingua | Periodo | SSD |
|---|---|---|---|---|---|
| Agent-based modelling | 6 | 40 | Inglese | Periodo non definito | GSPS-05/A |
| Causal inference in social and political science | 6 | 40 | Inglese | Periodo non definito | GSPS-02/A |
| Social network analysis | 6 | 40 | Inglese | Periodo non definito | GSPS-05/A |
| Text analytics and machine learning and large language models | 12 | 80 | Inglese | Periodo non definito | GSPS-02/A INFO-01/A |
| Final exam | 15 | 0 | Inglese | Periodo non definito | NN |
Attività a scelta e regole di composizione del piano didattico
2 - Students must earn 6 credits/ects for Elective substantial course
3 - Italian students or students with a certificate in Italian at level A2 or above must acquire 9 ECTS from an internship in the private sector, in government or public administration organisations or in academic institutions (including departmental laboratories and centres). Students who do not have a certificate in Italian at level A2 or above must acquire 3 ECTS of Italian language provided by the University Language Centre (SLAM), which reduces the ECTS for an internship to 6 ECTS.
Altre informazioni
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Info su ammissioni e immatricolazioni
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Strutture di riferimento
Contatti
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Via S. Sofia 9/1 - 20122 Milano (MI)
https://www.unimi.it/it/studiare/servizi-gli-studenti/segreterie-informastudenti - Referente del CdS:Prof. Flaminio Squazzoni
[email protected]
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- la prima rata ha importo uguale per tutti e si paga al momento dell’immatricolazione;
- la seconda rata varia in base al valore ISEE Università e al Corso di laurea;
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