Topics in Digital and Computational Demography
- Emilio Zagheni
- Diego Alburez-Gutierrez
- Samin Aref
- André Grow
- Sophie Lohmann
- Emilio Zagheni
Location: Online Course. Link tba.
Rapid increases in computational power and the explosion of Internet, social media and mobile phone use have radically changed our lives, the way we interact with each other and our behavior, including demographic choices and constraints. The digitalization of our lives has also led to the so-called “data revolution” that is transforming the social sciences.
Data science tools offer social scientists the opportunity to address core demographic questions in new ways. At the same time, demographic and social science methods enable researchers to make sense of new and complex data sources for which novel approaches and research designs may be needed.
The main goals for this course are:
- To introduce students to core demographic and social science methods that are essential to interpret digital trace data;
- To introduce students to core data science methods that are key to advance our understanding of population processes in the context of the increasing heterogeneity of data sources useful for demographic research;
- To introduce students to recent substantive advances in the field of Digital and Computational Demography, with emphasis on fostering critical thinking about modern demographic analysis and (big) data-driven discovery;
- To help students identify research questions in their own area of substantive interest that could be addressed with innovative data sources, and support them in the process of devising an appropriate research plan.
The course will be offered online. Each day, there will be one lecture and one discussion session. The lecture will be pre-recorded and made available ahead of time. Students are expected to watch the lecture carefully at their own pace and to complete the assignments before the discussion session, which will be held live every day from 16:00-17:30 CET (Central European Time). During the discussion session, homework assignments including hands-on computing exercises will be reviewed, assigned readings will be discussed and questions about the lecture will be addressed. Active participation of students is expected.
Each day, the lecture and discussion session will be presented by an experienced scholar in the field who will focus on a relevant research topic in which s/he is an expert.
In general students should expect to spend about 6-8 hours per day on the course (lectures, discussion sessions, readings, assignments).
The application deadline is 9 October 2020.