Zobrazeno 1 - 10
of 77
pro vyhledávání: '"Wiedemann, Gregor"'
Autor:
Rieger, Jonas, Yanchenko, Kostiantyn, Ruckdeschel, Mattes, von Nordheim, Gerret, Königslöw, Katharina Kleinen-von, Wiedemann, Gregor
Pre-trained language models (PLM) based on transformer neural networks developed in the field of natural language processing (NLP) offer great opportunities to improve automatic content analysis in communication science, especially for the coding of
Externí odkaz:
http://arxiv.org/abs/2312.16975
Autor:
Wiedemann, Gregor, Fedtke, Cornelia
Text, the written representation of human thought and communication in natural language, has been a major source of data for social science research since its early beginnings. While quantitative approaches seek to make certain contents measurable, f
Externí odkaz:
https://library.oapen.org/handle/20.500.12657/59856
Autor:
Kostikova, Aida, Paassen, Benjamin, Beese, Dominik, Pütz, Ole, Wiedemann, Gregor, Eger, Steffen
Solidarity is a crucial concept to understand social relations in societies. In this paper, we explore fine-grained solidarity frames to study solidarity towards women and migrants in German parliamentary debates between 1867 and 2022. Using 2,864 ma
Externí odkaz:
http://arxiv.org/abs/2210.04359
This article introduces to the interactive Leipzig Corpus Miner (iLCM) - a newly released, open-source software to perform automatic content analysis. Since the iLCM is based on the R-programming language, its generic text mining procedures provided
Externí odkaz:
http://arxiv.org/abs/2110.02708
Fine-tuning of pre-trained transformer networks such as BERT yield state-of-the-art results for text classification tasks. Typically, fine-tuning is performed on task-specific training datasets in a supervised manner. One can also fine-tune in unsupe
Externí odkaz:
http://arxiv.org/abs/2004.11493
Contextualized word embeddings (CWE) such as provided by ELMo (Peters et al., 2018), Flair NLP (Akbik et al., 2018), or BERT (Devlin et al., 2019) are a major recent innovation in NLP. CWEs provide semantic vector representations of words depending o
Externí odkaz:
http://arxiv.org/abs/1909.10430
De-identification is the task of detecting protected health information (PHI) in medical text. It is a critical step in sanitizing electronic health records (EHRs) to be shared for research. Automatic de-identification classifierscan significantly sp
Externí odkaz:
http://arxiv.org/abs/1906.05000
Publikováno v:
Proceedings of GermEval 2018, 14th Conference on Natural Language Processing (KONVENS 2018)
We investigate different strategies for automatic offensive language classification on German Twitter data. For this, we employ a sequentially combined BiLSTM-CNN neural network. Based on this model, three transfer learning tasks to improve the class
Externí odkaz:
http://arxiv.org/abs/1811.02906