Prerequisites: At least one statistics course, basic familiarity with R, Python or SAS.
Data from traditional sources (e.g., national population censuses, sample surveys, and administrative sources) on migration and immigration are limited in quantity and quality, and new alternatives have recently emerged. Some of these new types of "Big Data" are particularly promising for the study of migration-related phenomena. These include mobile phone call logs, Internet activity (e.g., Google searches, tracking of online media content use), geo-referenced social media activity, and other passively collected (mobile) data. This course is shared between the University of Maryland and University of Mannheim, and students will virtually attend the same class/lecture and then collaborate via online tools. Students from the two partnering universities will form international groups to collaboratively work on the collection and analysis of Big Data to answer immigration-related research questions.