Papers by Fynn Petersen-Frey
The D-WISE Tool Suite: Multi-Modal Machine-Learning-Powered Tools Supporting and Enhancing Digital Discourse Analysis (2023.acl-demo)
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| Challenge: | The D-WISE Tool Suite addresses limitations of current DH tools due to the ever-increasing amount of heterogeneous, unstructured, and multi-modal data in which discourses of contemporary societies are encoded. |
| Approach: | They propose to use D-WISE Tool Suite to analyze heterogeneous, unstructured, and multi-modal data in the Digital Humanities (DH) |
| Outcome: | The proposed tool leverages state-of-the-art machine learning technologies from Natural Language Processing and Com-puter Vision to ensure its usability for modernDH research. |
Extending the Discourse Analysis Tool Suite with Whiteboards for Visual Qualitative Analysis (2024.lrec-main)
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Tim Fischer, Florian Schneider, Fynn Petersen-Frey, Anja Silvia Mollah Haque, Isabel Eiser, Gertraud Koch, Chris Biemann
| Challenge: | Existing web-based platform for qualitative discourse analysis is limited to text, image, audio, video, and other multimodal data. |
| Approach: | They propose to extend existing web-based platform for digital qualitative discourse analysis with a new extension, Whiteboards, which offers a customizable view of the material and a wide range of actions that enable new ways of interacting with it. |
| Outcome: | The proposed extension facilitates reflection of the research process through sampling maps, creation of actor networks, and refining code taxonomies. |
Dataset of Quotation Attribution in German News Articles (2024.lrec-main)
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| Challenge: | Lack of annotated data for quotation attribution in news articles severely limits the quality and usability of possible systems. |
| Approach: | They propose a dataset for quotation attribution in German news articles using WIKINEWS and manually annotated quotes from 1000 articles. |
| Outcome: | The proposed dataset provides curated, high-quality annotations across 1000 documents (250,000 tokens) in a fine-grained annotation schema enabling various downstream uses for the dataset. |
Dataset of Student Solutions to Algorithm and Data Structure Programming Assignments (2022.lrec-1)
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| Challenge: | a dataset containing source code solutions to algorithmic programming exercises solved by students at the University of Hamburg is available under the permissive CC BY-NC 4.0 license. |
| Approach: | They present a dataset containing source code solutions to algorithmic programming exercises solved by students at the University of Hamburg. |
| Outcome: | The proposed dataset contains solutions to 21 programming tasks written in Java and Python and over 1500 individual solutions. |