Introduction to computational communication science - Modultafeln of TU Ilmenau

The grades will be based on the following:

1. class participation – 20% – students are encouraged to take part in the general discussions;

2. in-class presentation – 30% – students are required to make a few presentations during the semester based on research papers;

3. short paper – 50% – at the end of the semester students are required to submit a short paper (5 to 8 pages) on one of the topics discussed in the class.

R knowledge is not required, however appreciated.

During the course we will learn theoretical background behind the field of computational social and communication science.

Today, it is difficult to imagine our lives without Wikipedia, Google, Facebook, Instagram, iPhones, Wi-Fi, YouTube, Twitter, and other advances of the digital era. Spending most of our lives online, we leave digital footprints of our daily interactions and activities. Yes, all the pictures of kittens you liked last year on Facebook are now a part of traceable digital data available for social science research. We now have a unique opportunity to collect enormous amount of data on social behavior of human beings. However, the volume and heterogeneity of "big data" constitutes a challenging task for social scientists often discouraging them from analyzing precious material.

This course will focus mostly on social and communication science providing at the same time the very basic understanding of new computational methods that can be employed to collect and process ”big data”. We will learn how traditional methods of inquiry, such as interview and experiment, can be used in the context of new data sources. Important topics, such as ethics and availability of digital data, will be reviewed in the seminar. Students will also get a glimpse at the methods of automated text analysis, which has become an essential skill for every communication specialist. Knowledge received in the class can be further applied in the field of journalism, marketing, and advertising.

This course provides the necessary background to the theory of computational communications science. Students are recommended to attend the research module „Computational Communication Research: Human and Machine Biases in Digital Media” in parallel to the seminar in order to get hands-on experience of working with digital data and R.