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SO9D6-20: Social Data Science

Decorative

Timing and CATS

This module will run in Spring Term (2020/21) and is worth 20 CATS.

This module is a 3rd year (joint PGT) optional module available to Social Sciences, Humanities, and Science Departments. Everyone is welcome!

Further information.

Module Convenors: Dr Zofia Bednarowska and Prof Ulf Liebe

 

Module Description

What is so exciting about big data, data science and R? How can data science help towards a better understanding of social, political and economic processes? What does machine learning have to do with explaining societal outcomes, human behaviour and language usage? This module will develop students’ understanding of social data science, corresponding ethical issues as well as why data science is a useful tool for research conducted at universities, governmental and non-governmental organisations, as well as private companies in various sectors. Besides discussing applications of social data science to the study of sociological, political, economic, criminal and language phenomena, the module will provide students with the skills to conduct and critically reflect on social data science research. The module does not require prior knowledge of R and advanced statistical techniques. It will provide an introduction to R and include some basic applications of social data science, for example in the context of web data collection and analysis, as well as quantitative text analysis.

This module will develop your understanding of social data science, corresponding ethical issues as well as why data science is a useful tool for research conducted at universities, governmental and non-governmental organisations, as well as private companies in various sectors. Besides discussing applications of social data science to the study of sociological, political, economic, criminal and language phenomena, the module will provide you with the skills to conduct and critically reflect on social data science research.

Structure: 1 hour lecture + 2 hours practical workshop.

The module will be assessed by a 4000 words essay (100%).