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Timo Spinde
Timo Spinde
University of Göttingen / Media Bias Group
Verified email at media-bias-research.org - Homepage
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Year
Automated identification of bias inducing words in news articles using linguistic and context-oriented features
T Spinde, L Rudnitckaia, J Mitrović, F Hamborg, M Granitzer, B Gipp, ...
Information Processing & Management 58 (3), 102505, 2021
862021
Neural Media Bias Detection Using Distant Supervision With BABE - Bias Annotations By Experts
T Spinde, M Plank, JD Krieger, T Ruas, B Gipp, A Aizawa
Findings of the Association for Computational Linguistics: EMNLP 2021, 1166-1177, 2021
772021
MBIC - A Media Bias Annotation Dataset Including Annotator Characteristics
T Spinde, L Rudnitckaia, K Sinha, F Hamborg, B Gipp, K Donnay
Proceedings of the iConference 2021, 2021
502021
Enabling news consumers to view and understand biased news coverage: a study on the perception and visualization of media bias
T Spinde, F Hamborg, K Donnay, A Becerra, B Gipp
Proceedings of the ACM/IEEE joint conference on digital libraries in 2020 …, 2020
492020
An integrated approach to detect media bias in german news articles
T Spinde, F Hamborg, B Gipp
Proceedings of the ACM/IEEE joint conference on digital libraries in 2020 …, 2020
312020
Identification of Biased Terms in News Articles by Comparison of Outlet-specific Word Embeddings
T Spinde, L Rudnitckaia, F Hamborg
Proceedings of the iConference 2021. Springer Nature, Virtual Event China, 2021
282021
Media bias in german news articles: A combined approach
T Spinde, F Hamborg, B Gipp
Joint European Conference on Machine Learning and Knowledge Discovery in …, 2020
262020
Introducing MBIB-the first media bias identification benchmark task and dataset collection
M Wessel, T Horych, T Ruas, A Aizawa, B Gipp, T Spinde
Proceedings of the 46th International ACM SIGIR Conference on Research and …, 2023
242023
Exploiting transformer-based multitask learning for the detection of media bias in news articles
T Spinde, JD Krieger, T Ruas, J Mitrović, F Götz-Hahn, A Aizawa, B Gipp
International conference on information, 225-235, 2022
242022
A domain-adaptive pre-training approach for language bias detection in news
JD Krieger, T Spinde, T Ruas, J Kulshrestha, B Gipp
Proceedings of the 22nd ACM/IEEE joint conference on digital libraries, 1-7, 2022
232022
Towards a reliable ground-truth for biased language detection
T Spinde, D Krieger, M Plank, B Gipp
2021 ACM/IEEE Joint Conference on Digital Libraries (JCDL), 324-325, 2021
192021
An interdisciplinary approach for the automated detection and visualization of media bias in news articles
T Spinde
2021 International Conference on Data Mining Workshops (ICDMW), 1096-1103, 2021
182021
Do You Think It's Biased? How To Ask For The Perception Of Media Bias
T Spinde, C Kreuter, W Gaissmaier, F Hamborg, B Gipp, H Giese
2021 ACM/IEEE Joint Conference on Digital Libraries (JCDL), 61-69, 2021
182021
TASSY—A Text Annotation Survey System
T Spinde, K Sinha, N Meuschke, B Gipp
2021 ACM/IEEE Joint Conference on Digital Libraries (JCDL), 322-323, 2021
162021
How do we raise media bias awareness effectively? Effects of visualizations to communicate bias
T Spinde, C Jeggle, M Haupt, W Gaissmaier, H Giese
Plos one 17 (4), e0266204, 2022
152022
A benchmark of pdf information extraction tools using a multi-task and multi-domain evaluation framework for academic documents
N Meuschke, A Jagdale, T Spinde, J Mitrović, B Gipp
International Conference on Information, 383-405, 2023
142023
The media bias taxonomy: A systematic literature review on the forms and automated detection of media bias
T Spinde, S Hinterreiter, F Haak, T Ruas, H Giese, N Meuschke, B Gipp
arXiv preprint arXiv:2312.16148, 2023
92023
Omission of information: Identifying political slant via an analysis of co-occurring entities
J Ehrhardt, T Spinde, A Vardasbi, F Hamborg
Werner Hülsbusch 74, 80-93, 2021
92021
Do you think it’s biased? how to ask for the perception of media bias. In 2021 ACM/IEEE Joint Conference on Digital Libraries (JCDL)
T Spinde, C Kreuter, W Gaissmaier, F Hamborg, B Gipp, H Giese
IEEE, 2021
82021
How can the perception of media bias in news articles be objectively measured? Best practices and recommendations using user studies
T Spinde, C Kreuter, W Gaissmaier, F Hamborg, B Gipp, H Giese
Proceedings of the ACM/IEEE Joint Conference on Digital Libraries (JCDL …, 2021
72021
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