• Navid Hassanpour

• Daniel Kronovet
• Luronne Vaval

• [Kay Kastner](emailto: [email protected])

##Course Description:

This course is designed to equip QMSS students with tools from datascience for collecting, processing, and presenting new modes of data. The focus of the courseis on collection, processing, and visualization of novel modes of data (Big Data analysis in the popular discourse). Students will engage in the empirical analysis of a major real world devent, the U.S. Presidential Elections' Primaries during this course, in order to put the methods they learn into practice. During the course students are expected to work on a project that involves

• harvesting data from web platforms such as Twitter API,
• running analysis with social scientific import on the data they collected (R and Python), and
• using effective visualization methodology for

1. Interactive web-based design (RShiny and D3)
2. Social network analysis (D3 and RShiny)
3. GIS (D3 and RShiny)
4. Text analytics and visualization (in R)
5. Statistical analysis and visualization (R's ggplot2, RShiny).

Familiarity with relevant software tools would be a plus, but is not necessary as we will have tutorials on the essential software through the semester.

###Lecture 1

###Lecture 2

###Lecture 3

###Lecture 4

###Lecture 5

###Lecture 6

###Lecture 7

###Lecture 8