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NEBULA: Nutzerzentrierte KI-basierte Erkennung von Fake-News und Fehlinformationen

Overview

The goal of this interdisciplinary project is the transparent, AI-based detection of Fake News and false information in security-relevant situations and a presentation of the detection results that is suitable for the target audience and boosts the audiences media literacy.

Funding program

This work is supported by the German Federal Ministry of Education and Research (BMBF) under the grant no 13N16364.

Key Facts

Grant Number:
13N16364
Project duration:
07/2022 - 06/2025
Funded by:
BMBF
Websites:
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More Information

Principal Investigators

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Prof. Dr. Axel-Cyrille Ngonga Ngomo

Transregional Collaborative Research Centre 318

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Project Team

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Dr. Michael Röder

Data Science / Heinz Nixdorf Institute

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Ana Morim da Silva

Data Science / Heinz Nixdorf Institute

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Cooperating Institutions

Technische Universität Darmstadt (TUDA)

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PEASEC – Science and Technology for Peace and Security

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Wirtschaftsinformatik und Neue Medien der Universität Siegen

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NanoGiants GmbH

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Hochschule Bonn-Rhein-Sieg (H-BRS)

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Publications

ExPrompt: Augmenting Prompts Using Examples as Modern Baseline for Stance Classification
U. Qudus, M. Röder, D. Vollmers, A.-C. Ngonga Ngomo, in: Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, ACM, 2024, pp. 3994–3999.
FaVEL: Fact Validation Ensemble Learning
U. Qudus, M. Röder, F.L. Tatkeu Pekarou, A.A. Morim da Silva, A.-C. Ngonga Ngomo, in: M. Rospocher, Mehwish Alam (Eds.), EKAW 2024, 2024.
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