| Study program / study programs: Advanced data analytics |
| Course: Big Data in Social Sciences |
| Teacher(s): Jelena Pešić, Irena Petrović, Jelisaveta Petrović, Dragan Stanojević, Oliver Tošković |
| Course status: Elective |
| ECTS points: 7 |
| Prerequisites: / |
| Course objective(s): The objective of the Big Data in Social Sciences course is to introduce students to the social, ethical and methodological challenges that stem out from the use of big social data, as well as to familiarize them with the ways of overcoming these challenges in social sciences. |
| Learning outcomes: Knowledge of different types and ways of using big data in social sciences- Knowledge of methodological possibilities and restrictions on the use of big data in social sciences- Familiarization with the ways of combined use of big data and “small / micro” data sets collected by standard social research techniques (survey research, interviews, observation, etc.)- Knowledge of ethical standards in using big social data- Awareness of the legal aspects of the use of big social data- Developed ability of critical assessment of big social data |
| Course structure and content: Types, sources and quality of big social data- Social implications of using big data: digital inequalities and divisions, surveillance and freedom, privacy concerns, social scoring system, etc.- The use of big data in social sciences in different fields: political behavior, consumer practices, crime, forms of communication through social networks, socio-spatial phenomena, etc.- Methodological aspects of using big data in social sciences – representativeness, bias, measurement and sampling errors, decontextualization, etc.- Combining different sets of data: “small / micro” and large in the analysis of social phenomena.- Ethical aspects of the use of big data in social sciences.- Legal frameworks for the use of big social data with a special emphasis on the European Union legislation (GDPR). |
| Literature/Readings: Foster, I et al. (2017) Big Data and Social Sciences – A Practical Guide to Methods and Tools, London: CRC Press. (selected chapters) Hoeren, T, Kolany-Raiser (eds.) (2018) Big Data in Context – Legal, Social and Technological Insights. Springer Open. (selected chapters) Petrović, J. (2018) „Veliki“ podaci – veliki izazov za sociologiju? Sociologija 60(3):557-582. Boyd, D., Crawford, K. (2012) Critical Questions for Big Data, Information, Communication and Society 15(5):662-679. |
| The number of class hours per week: Lectures: 5 Labs: 0 Workshops: 1 Research study: 2 Other classes: 0 |
| Teaching methods: Individual and group work; lectures and labs. |
| Evaluation/Grading (maximum 100 points): Pre-exam requirements (Development of the research design and Power point presentation of the research phases): 30 Final exam (Developed design of the research on selected social phenomenon using big data): 70 |
