My core research topic is about topics - probabilistic topic models, to be precise!
Topic models typically detect topics by co-occurrences of words on text documents. I include contexts - such as geographical coordinates - to detect co-occurrences of words in documents and the context space.
Besides topic modelling, I'm generally interested in probabilistic modelling for aiding research in the social sciences.
In my free time, I'm politically active (e.g. fighting for data privacy), am member of a humanistic club and go biking
|Probabilistic models for context in social media|
|Topic model tutorial: A basic introduction on latent Dirichlet allocation and extensions for web scientists|
Christoph Carl Kling, Lisa Posch, Arnim Bleier, Laura Dietz. WebSci
|An exploration of fetish social networks and communities.|
Damien Fay, Hamed Haddadi, Michael C. Seto, Han Wang, Christoph Carl Kling.
|Voting Behaviour and Power in Online Democracy: A
Study of LiquidFeedback in Germany's Pirate Party|
Christoph Carl Kling, Jérôme Kunegis, Heinrich Hartmann, Markus Strohmaier, Steffen Staab. Proc. Int. Conf. on Weblogs and Social Media
|Glaubwürdigkeit und Vertrauen von Online-News|
Ines C. Vogel, Jutta Milde, Karin Stengel, Steffen Staab, Christoph Carl Kling, Jérôme Kunegis.
|Detecting Non-Gaussian Geographical Topics in Tagged Photo Collections|
Christoph C. Kling, Jerome Kunegis, Sergej Sizov, Steffen Staab. WSDM'14: Proceedings of the 7th International Conference on Web Search and Data Mining
|Detecting Culture in Coordinates: Cultural Areas in Social Media|
Christoph Kling, Thomas Gottron. DETECT'11: Proceedings of the International Workshop on DETecting and Exploiting Cultural diversiTy on the Social Web
|Virtual Field Research with Social Media: A Pilot Case of Biometeorology|
Christoph Kling, Sergej Sizov, Steffen Staab. Poster Proceedings of ACM WebSci '11 - Third Int. Conference on Web Science