Through social media applications such as Twitter, Facebook and blogs, the opportunities for public communication have expanded. Journalistic "gatekeeper" on the Internet are no longer the central mediator of topics and opinions. In principle, now individual and collective actors of all types participate as a speaker at public discourses. Hence, processes and structures of the general public are changed. Topics careers and opinions take other routes than in traditional media. At the same time, the Internet offers a higher level of transparency. In addition, digital texts can be analysed automatically. The goal of the project network is to develop and evaluate such an automated process in order that these approaches can be applied in answering questions about online communication studies.
The quantitative content analysis as a standard manual method of communication science is very time-consuming and costly. This is no less true for qualitative method of discourse analysis, which are used in other social sciences. To address this limitation, in the joint project, the two communication scienctists collaborate with academics from two other subjects who introduce different methodological approaches. Methods of the information systems research allow the collection of large amounts of data from various social media (data tracking). Besides, there are techniques to structure the data using automated network analysis. Computational linguistics are equipped with methods for the analysis of sentiment and discourse qualities. In addition, an automated method of content analysis is developed that is based on inductive text classification. Manual methods are used to complement and evaluate. Overall, it should thus be possible to analyze public discourses on the micro, meso and macro levels diversely and comparatively.