Current Challenges in Digital Communication Research - Interactive curriculae of TU Ilmenau
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| module properties Current Challenges in Digital Communication Research in degree program Master Media and Communication Science 2021 | |
|---|---|
| module number | 200832 |
| examination number | 2500591 |
| department | Department of Economic Sciences and Media |
| ID of group | 2559 (Kommunikationswissenschaft mit Schwerpunkt Computational Communication Science) |
| module leader | Prof. Dr. Emese Domahidi |
| term | summer term only |
| language | Englisch |
| credit points | 5 |
| on-campus program (h) | 22 |
| self-study (h) | 128 |
| obligation | elective module |
| exam | alternative examination performance |
| details of the certificate | Students have to participate actively in discussions. Students are required to develop a research project and present their projects. Students are required to submit a research paper based on their research projects. |
| link to Moodle course | https://moodle2.tu-ilmenau.de/course/view.php?id=4681 |
| teacher | siehe Beschreibungen des wählbaren Angebots |
| signup details for alternative examinations | This module contains at least one alternative exam part. Please note that this must usually be registered at the beginning of the semester in which it is offered. |
| maximum number of participants | 12 |
| previous knowledge and experience | Familiarity with empirical methods and quantitative data analysis in communication research. Familiarity with computational methods and data analysis software skills (e.g. R, Python). It is highly recommended to attend in advance the specialization module "Introduction to computational communication science" to be familiar with the computational methods required. |
| learning outcome | Students can review relevant literature on specific topics in digital communication and computational communication science. Students can develop a research project to analyze relevant research questions in digital communication via computational communication science methods. Students are able to apply different computational methods (e.g. sentiment analysis, supervised machine learning) during the course. Students can critically evaluate the obtained results and discuss them based on previous research. Students can describe and present their projects. |
| content | The specialization module will deal with current topics and research challenges in digital communication research. For example, based on previously defined data sets students will develop research questions and apply computational methods to analyze them accordingly or they deal in depth with current issues (e.g. ethical challenges) or theoretical challenges related to the field of Computational Communication Science. |
| media of instruction and technical requirements for education and examination in case of online participation | All materials will be made available on Moodle. |
| literature / references | Will be announced each semester. |
| evaluation of teaching | |