Computational Social Science  (SCS1)

In this programme we value undergraduate training which equips students with a clear understanding of the interdisciplinary challenges of the field of computational social science. In particular this new UCD BSc degree in Computational Social Science will enable students, whose orientation is towards the social sciences, to couple these core interests with their strong aptitude for computational and analytical training.

We value and support our students' entrepreneurial and innovative strengths as we understand that these characteristics will enable students to make the most of training on this programme. UCD graduates of the new BSc in Computational Social Science will be very well placed to avail of the many new and exciting career opportunities emerging as part of the data revolution impacting on our society and economy. In particular our core modules will encourage students to explore how computational social science can provide new insights and enrich our understanding of observed and new or emergent social phenomena.

In the programme we value training which is both pragmatic and professional in its orientation. We aim to encourage and support students to uphold the highest standards of data management and application in their work, both on and off campus. Students will be encouraged to explore opportunities available to combine their academic training with opportunities to gain valuable career-oriented skills and professional experience. We can also facilitate students who may want to focus on a much deeper academic engagement through advanced and more specialised modules also available.

1 - Demonstrate a broad understanding of the social sciences and their multidisciplinary nature.
2 - Demonstrate a core knowledge and understanding of the fundamentals of computational social science.
3 - Synthesise, evaluate, interpret and report theories and evidence in an open, analytical and critical manner.
4 - Apply problem solving skills in a variety of different contexts
5 - Apply appropriate computational social science and social data analytic techniques to address domain specific research problems.
6 - Work effectively and responsibly, using professional techniques, tools and technologies, as an individual and in teams.
7 - Demonstrate best practice in the collection, manipulation and storage of data, some of which may be sensitive; Responsible and professional use of data and reporting of research results.
8 - Demonstrate an awareness of the regulatory governance framework and principles of ethical practice in the social sciences and how these principles should be applied.
9 - Communicate effectively using written, quantitative, visual and oral method.
10 - Discuss, present and communicate their research ideas, data and results within a group setting and in one-to-one communication.
11 - Demonstrate awareness and aptitude to engage in ongoing training and upskilling
12 - Recognize and appreciate that the field of computational social science and social data analytics is a fast developing science wherein new technologies and analytical techniques are emerging rapidly and professional norms require engagement with this process.

During the third year, trimester-long study opportunities will be offered in a number of international partner universities.

This course is designed to prepare students for employment opportunities related to the curation and analysis of social big data as well as deploying computational methods such as simulation and machine learning to social scenarios for better policy testing and development. With the increasing demand for social data science expertise, graduates of this course can expect to find employment in a variety of sectors, including Information Technology companies such as Google, Deepmind, Microsoft, LinkedIn, Accenture, Twitter, and Facebook, as well as industries such as Finance, Insurance, Manufacturing, Retail and Energy. Public sector and NGO’s are among the other markets where social data scientists are in high demand.

Graduate study opportunities include Social Data Science, Social Sciences, Mathematics and Statistics, Computer Science and Informatics, and other interdisciplinary programmes.

UCD School of Sociology

e. sociology@ucd.ie

Stage 3

Please ensure that you register to a minimum of 20 credits in total from the options list below. If you are studying abroad (Erasmus/non EU exchange) and/or undertaking an internship, please see registration guidelines here.

Stage 4

Please ensure that you register to a minimum of 5 credits in total from the options list below.

Note: In order to complete your Undergraduate degree, you must earn at least 40 credits at level 3 or above. It is your responsibility to ensure that you meet this requirement. Note: You may have taken some level 3 modules in stage 3 already.

See the UCD Assessment website for further details

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Module Weighting Info