Introduction to computational communication science - Modultafeln of TU Ilmenau
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|subject properties Introduction to computational communication science in major Master Medien- und Kommunikationswissenschaft/Media and Communication Science 2013|
|department||Department of Economic Sciences and Media|
|ID of group||2559 (Kommunikationswissenschaft mit Schwerpunkt Computational Communication Science)|
|subject leader||Prof. Dr. Emese Domahidi|
|on-campus program (h)||22|
|exam||alternative examination performance|
|details of the certificate|
The grades will be based on the evaluation of a short term paper.
|Signup details for alternative examinations||Die Anmeldung zur alternativen semesterbegleitenden Abschlussleistung erfolgt über das Prüfungsverwaltungssystem (thoska) außerhalb des zentralen Prüfungsanmeldezeitraumes. Die früheste Anmeldung ist generell ca. 2-3 Wochen nach Semesterbeginn möglich. Der späteste Zeitpunkt für die An- oder Abmeldung von dieser konkreten Abschlussleistung ist festgelegt auf den (falls keine Angabe, erscheint dies in Kürze):|
|maximum number of participants||30|
|previous knowledge and experience|
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”. Important topics, such as ethics and availability of digital data, will be reviewed in the seminar. Students will 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 take the research modules „Computational Communication Research” in parallel to the seminar in order to get hands-on experience of working with digital data and R.
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