Timo Spinde
Doctoral Researcher

SHORT BIOGRAPHY
After finishing a double bachelor’s degree in ”Internet Computing” (Computer Science) and “Media and Communications”, I followed up on my research interest in data science and data driven journalism by pursuing a master’s degree in ”Social and Economic Data Analysis”. Within my doctoral research I focus on news analysis and am working on a system to automatically detect media bias.
RESEARCH INTERESTS
My research interests are:
- Media bias analysis
- Natural Language Processing (NLP)
- Network Analysis
TEACHING & PROJECTS
We offer many different projects within the domain of media bias and NLP. You can always contact me, and I’ll give you an overview.
SHORT CV
09/2022 – present
Doctoral Researcher
Universität Göttingen
01/2020 – 09/2022
Doctoral Researcher
Bergische Universität Wuppertal
10/2016 – 02/2019
Social and Economic Data Analysis, M.Sc.
University of Konstanz
10/2018 – 02/2019
Visiting Researcher
Technion Haifa & University of Haifa, Israel
04/2016 – 08/2016
Data Scientist (Internship)
Celonis Ltd., München
10/2012 – 02/2019
Scholarship Hanns-Seidel-Stiftung
Journalism support program
04/2012 – 12/2015
Media and Communications, B.A., and Internet Computing, B.Sc.
University of Passau
SELECTED PUBLICATIONS
- T. Spinde, M. Plank, J.-D. Krieger, T. Ruas, B. Gipp, A. Aizawa, “Neural Media Bias Detection Using Distant Supervision With BABE – Bias Annotations By Experts”, in Findings of the Association for Computational Linguistics: EMNLP 2021, Dominican Republic, 2021. DOI: 10.18653/v1/2021.findings-emnlp.101
- T. Spinde, “An Interdisciplinary Approach for the Automated Detection and Visualization of Media Bias in News Articles”, in Proceedings of the 2021 IEEE International Conference on Data Mining Workshops (ICDMW), New Zealand, 2021. DOI: doi:10.1109/ICDMW53433.2021.00144
- T. Spinde, J. D. Krieger, T. Ruas, J. Mitrović, F. Götz-Hahn, A. Aizawa, B. Gipp, “Exploiting Transformer-based Multitask Learning for the Detection of Media Bias in News Articles”. In: Proceedings of the iConference 2022. DOI: doi:https://doi.org/10.1007/978-3-030-96957-8_20