Hiroshima University

What you'll study

This interdisciplinary programme covers methods and applications at the intersection of data science and the social sciences. Core study areas include statistical modelling, machine learning for social data, causal inference, computational social science, data visualisation and ethics of data use. Students also study social theory, research design, and domain-focused modules such as urban analytics, political behaviour, public policy analysis, and health and social-care analytics.

The curriculum typically combines compulsory methodological courses with elective seminars and a supervised research project (thesis). Practical components emphasise hands-on training in programming (Python/R), database management, geospatial analysis, and text and network analysis. Seminars and workshops foster skills in data collection, reproducible research, privacy-aware practices and communicating findings to non-technical stakeholders.

• Statistical Methods for Social Research
• Machine Learning and Predictive Analytics for Social Data
• Causal Inference and Experimental Design
• Computational Social Science and Network Analysis
• Text Mining and Natural Language Processing
• Geospatial Analysis and Urban Data
• Data Ethics, Privacy and Governance
• Research Methods and Thesis Project

Entry requirements

Applicants are normally expected to have a bachelor’s degree or equivalent in a related discipline such as social sciences, humanities, economics, statistics, mathematics, computer science or engineering. Strong quantitative preparation is desirable; applicants without formal quantitative training should demonstrate relevant coursework or practical experience (e.g. statistics, programming, econometrics).

Other typical requirements include a transcript of academic records, a statement of purpose outlining research interests, and two academic or professional references. International applicants will need to demonstrate proficiency in English; additional language support may be available within the university. Where required, applicants may be asked to attend an interview or submit a research proposal for the master’s thesis.

Career prospects

Graduates are prepared for roles that bridge social inquiry and data-driven decision-making. Common career paths include data analyst or data scientist roles in government agencies, public policy think-tanks, NGOs and international organisations; policy analyst positions drawing on empirical evidence to inform public programmes; and research or technical positions in academia and private-sector firms focused on social impact, marketing analytics, urban planning, health informatics or human-centred AI.

The programme also provides a solid foundation for further doctoral study in social data science, computational social science or related interdisciplinary fields. Emphasis on applied projects and communication equips graduates to work in multi-disciplinary teams and to translate complex analyses into actionable recommendations.

Why study at Hiroshima University

Hiroshima University is a comprehensive national university with established strengths in interdisciplinary research and social science methods. The Social Data Science programme benefits from collaborative links across faculties—including social sciences, information science and public policy—giving students access to diverse supervisors and applied research projects.

Students gain practical experience through laboratory courses, workshops and collaborations with local government and community organisations in the Hiroshima region, providing opportunities to work on real-world datasets and policy-relevant problems. The university’s research environment emphasises ethical data use, international collaboration and a supportive setting for both domestic and international students.