User Experience Design for Automatic Credibility Assessment of News Content About COVID-19

descriptionPublicationkeyboard_double_arrow_right Part of book or chapter of book , Presentation , Other literature type , Article , Preprint , Conference object 01 Jan 2022Embargo end date: 01 Jan 2022 English Publisher:Springer Nature Switzerland

Authors: Konstantin Schulz; Jens Rauenbusch; Jan Fillies; Lisa Rutenburg; Dimitrios Karvelas; Georg Rehm;

doi: 10.1007/978-3-031-22131-6_11 , 10.5281/zenodo.6786009 , 10.5281/zenodo.6786008 , 10.48550/arxiv.2204.13943

arXiv: 2204.13943

User Experience Design for Automatic Credibility Assessment of News Content About COVID-19

- Summary
- Subjects
- Metrics

Abstract

The research presented in this paper is funded by the German Federal Ministry of Education and Research (BMBF) through the project PANQURA (http://qurator.ai/panqura; grant no. 03COV03E).

Slides for a talk at the HCII 2022 conference

Related Organizations

German Research Centre for Artificial Intelligence
Germany

Keywords

FOS: Computer and information sciences, Computer Science - Computation and Language, Computer Science - Artificial Intelligence, I.2.7, H.5.2; I.2.7, Computer Science - Human-Computer Interaction, 68-04, Human-Computer Interaction (cs.HC), credibility, H.5.2, usability, Artificial Intelligence (cs.AI), covid-19, news, Computation and Language (cs.CL)

Impact byBIP!

	selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	2
	popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.	Average
	influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	Average
	impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.	Average