Papers by Tim Fischer

6 papers
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.
HatePRISM: Policies, Platforms, and Research Integration. Advancing NLP for Hate Speech Proactive Mitigation (2025.findings-acl)

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Challenge: Existing approaches to manage hate speech rely on reactive measures such as blocking or suspending offensive messages . despite regulations imposed by nations and social media platforms, hateful content remains a challenge .
Approach: They propose a framework for automated hate speech moderation based on different strategies . they examine hate speech regulations and strategies from three perspectives .
Outcome: The proposed framework could be based on a combination of country regulations, social platform policies, and NLP research datasets.
Extending the Discourse Analysis Tool Suite with Whiteboards for Visual Qualitative Analysis (2024.lrec-main)

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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.
Concept Over Time Analysis: Unveiling Temporal Patterns for Qualitative Data Analysis (2024.naacl-demo)

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Challenge: Concept Over Time Analysis is a machine-learning-based feature that allows users to define, refine, and visualize concepts of interest within an interactive interface.
Approach: They propose to extend the Discourse Analysis Tool Suite with Concept Over Time Analysis extension that allows users to define, refine, and visualize their concepts of interest within an interactive interface.
Outcome: The proposed system allows users to define, refine, and visualize their concepts of interest within an interactive interface.
LT Expertfinder: An Evaluation Framework for Expert Finding Methods (N19-4)

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Challenge: LT Expertfinder is a web-based tool for expert finding and expert profiling.
Approach: They propose a web-application that enables qualitative comparison between different ranking methods . LT Expertfinder provides detailed expert profiles linked to Wikidata and Google Scholar .
Outcome: The LT Expertfinder is a web-based tool for expert finding and evaluation.
AnnoPlot: Interactive Visualizations of Text Annotations (2024.eacl-demo)

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Challenge: Annotation projects face challenges in data quality and validity, authors argue .
Approach: They propose an open-source web application that analyzes, manages, and visualizes annotated text data.
Outcome: The proposed application is open-source and promotes transparency and user control . it offers comprehensive views of span annotations and category systems without training or classification model .

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