The Computational Communication Science Group primarily investigates the usage of digital media and its effects on individuals and society. In addition to classical communication science methods, the group focuses on the application and evaluation of computational approaches in communication studies.

Cognitive and Algorithmic Biases in Digital Media

In the research project, we examine the emergence of cognitive and algorithmic biases in digital media. Specific characteristics of online media environments, such as an increasing personalization of news selection, the visibility of users’ social networks, various types of digital content, and different user habits, may enhance selective and biased perception, as well as influence the distribution of content in modern media. Consequently, it may lead to the formation of highly homogeneous and preference-consistent information clusters, which stand in contrast with versatile knowledgeability of citizens and democratic opinion pluralism.

Social Consequences of Online Media Use

Our research group studies the relationship between digital media consumption and users’ social resources, especially with regard to individuals’ professional sphere. The increasing demand for information and support among employees in digital work environments is provided by online social media (OSM), such as enterprise social networking and external job-related or general OSM. Using online social media, users receive and exchange information with their social networks that results in various forms of social support essential in private and professional contexts.

Government crisis communication and citizen’s reaction

We study how governments communicate during crisis events and how citizens respond to government messages, e.g., by spreading misinformation on the Internet, opinion leadership in the community, etc. By combining computational methods and theories of crisis communication, we aim not only to reflect on current crises, but also to comprehensively prepare for the next crisis.