Alexander Mehler’s research interests include automatic analysis and synthesis of language and multimodal data in spoken and written communication. To this end, he studies multimodal and multiplex networks derived from social and communication networks using models of language evolution, machine learning, and complex network theory. He is particularly interested in measurement models that help overcome end-to-end learning and its issues. This involves models of multimodal semantics that focus on the explicit modelling of sign structures. Alexander Mehler develops and tests quantitative methods and machine learning models that merge with virtual and augmented reality. The goal of this research is to ground multimodal semantics based on human behaviour in virtual worlds.
About
Goethe University Frankfurt
mehler@em.uni-frankfurt.de
Project
Selected Publications
Mehler, A., Gleim, R., Gaitsch, R., Uslu, T. & Hemati, W. (2020, online). From Topic Networks to Distributed Cognitive Maps: Zipfian Topic Universes in the Area of Volunteered Geographic Information. Complexity, vol. 4, pp. 1-47. DOI: 10.1155/2020/4607025
Mehler, A., Hemati, W., Welke, P., Konca, M. & Uslu, T. (2020, online). Multiple Texts as a Limiting Factor in Online Learning: Quantifying Dissimilarities of Knowledge Networks across Languages. Frontiers in Education (Digital Education), pp. 1-31. DOI: 10.3389/feduc.2020.562670
Mehler A., Gleim, R., Lücking, A., Uslu, T., & Stegbauer, Ch. (2018). „On the Self-similarity of Wikipedia Talks: a Combined Discourse-analytical and Quantitative Approach“. In: Glottometrics 40, pp. 1–45
Mehler, A., Lücking. A., & Abrami, G. (2014). „WikiNect: Image Schemata as a Basis of Gestural Writing for Kinetic Museum Wikis“. In: Universal Access in the Information Society, pp. 1–17. DOI: 10.1007/s10209-014-0386-8
Mehler, A., Lücking, A. & Menke, P. (2012). „Assessing Cognitive Alignment in Different Types of Dialog by means of a Network Model“. In: Neural Networks 32, S. 159–164. DOI: 10.1016/j.neunet.2012.02.013