Gregor Wiedemann
Gregor Wiedemann
Leibniz-Institute for Media Research | Hans-Bredow-Institut
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Cited by
Applying LDA topic modeling in communication research: Toward a valid and reliable methodology
D Maier, A Waldherr, P Miltner, G Wiedemann, A Niekler, A Keinert, ...
Computational methods for communication science, 13-38, 2021
Opening up to Big Data: Computer-Assisted Analysis of Textual Data in Social Sciences
G Wiedemann
Historical Social Research 38 (4), 332-357, 2013
Does BERT Make Any Sense? Interpretable Word Sense Disambiguation with Contextualized Embeddings
G Wiedemann, S Remus, A Chawla, C Biemann
15th Conference on Natural Language Processing (KONVENS), 2019
Text Mining for Qualitative Data Analysis in the Social Sciences. A Study on Democratic Discourse in Germany
G Wiedemann
Springer, 2016
Text Mining in den Sozialwissenschaften. Grundlagen und Anwendungen zwischen qualitativer und quantitativer Diskursanalyse
M Lemke, G Wiedemann
Springer, 2016
Transfer Learning from LDA to BiLSTM-CNN for Offensive Language Detection in Twitter
G Wiedemann, E Ruppert, R Jindal, C Biemann
GermEval 2018@14th Conference on Natural Language Processing (KONVENS), 85-94, 2018
UHH-LT at SemEval-2020 Task 12: Fine-Tuning of Pre-Trained Transformer Networks for Offensive Language Detection
G Wiedemann, SM Yimam, C Biemann
International Workshop on Semantic Evaluation (SemEval), 2020
Postdemokratie und Neoliberalismus: zur Nutzung neoliberaler Argumentationen in der Bundesrepublik Deutschland 1949-2011; ein Werkstattbericht
G Wiedemann, M Lemke, A Niekler
ZPTh - Zeitschrift für Politische Theorie 4 (1), 99-115, 2013
Adversarial Learning of Privacy-Preserving Text Representations for De-Identification of Medical Records
M Friedrich, A Köhn, G Wiedemann, C Biemann
Association for Computational Linguistics (ACL), 5829-5839, 2019
Topics and topical phases in German social media communication during a disaster
S Gründer-Fahrer, A Schlaf, G Wiedemann, G Heyer
Natural Language Engineering 24 (2), 221-264, 2018
Leipzig Corpus Miner-A Text Mining Infrastructure for Qualitative Data Analysis
A Niekler, G Wiedemann, G Heyer
Terminology and Knowledge Engineering (TKE), 10, 2014
Quantifying insightful problem solving: A modified compound remote associates paradigm using lexical priming to parametrically modulate different sources of task difficulty
M Becker, G Wiedemann, S Kühn
Psychological research 84 (2), 528-545, 2020
Proportional classification revisited: Automatic content analysis of political manifestos using active learning
G Wiedemann
Social Science Computer Review 37 (2), 135-159, 2019
How document sampling and vocabulary pruning affect the results of topic models
D Maier, A Niekler, G Wiedemann, D Stoltenberg
Computational Communication Research 2 (2), 139-152, 2020
Content Analysis between Quality and Quantity
M Lemke, A Niekler, GS Schaal, G Wiedemann
Datenbank-Spektrum 15 (1), 7-14, 2015
Hands-On: A Five Day Text Mining Course for Humanists and Social Scientists in R
G Wiedemann, A Niekler
Workshop on Teaching NLP for Digital Humanities (Teach4DH@GSCL) 2017, 57-65, 2017
Analyse qualitativer Daten mit dem "Leipzig Corpus Miner"
G Wiedemann, A Niekler
Text Mining in den Sozialwissenschaften, 63-88, 2016
Text Mining für die Analyse qualitativer Daten. Auf dem Weg zu einer Best Practice?
G Wiedemann, M Lemke
Text Mining in den Sozialwissenschaften, 397-419, 2016
Multi-modal page stream segmentation with convolutional neural networks
G Wiedemann, G Heyer
Language Resources and Evaluation 55 (1), 127-150, 2021
New/s/leak 2.0–Multilingual Information Extraction and Visualization for Investigative Journalism
G Wiedemann, SM Yimam, C Biemann
International Conference on Social Informatics (SocInfo), 313-322, 2018
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