CaptureBias

Supporting Media Scholars with Ambiguity-Aware Bias Representation for News Videos

Conference paper (2018)

Authors

M. de Jong Web Information Systems - EEMCS
P. Mavridis Vrije Universiteit Amsterdam
Lora Aroyo Universiteit Leiden
A. Bozzon Web Information Systems - EEMCS
Jesse de Vos Nederlands Instituut voor Beeld en Geluid
Johan Oomen Nederlands Instituut voor Beeld en Geluid
Antoaneta Dimitrova Universiteit Leiden
Alec Badenoch Universiteit Utrecht
Research Group
Web Information Systems (EEMCS) (TU Delft)
Copyright: © 2018 M. de Jong, P. Mavridis, Lora Aroyo, A. Bozzon, Jesse de Vos, Johan Oomen, Antoaneta Dimitrova, Alec Badenoch
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Published Date

2018

Language

English

Reuse Rights

Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.

Faculty

Electrical Engineering, Mathematics and Computer Science

Department

Software Technology

Research Group

Web Information Systems

Abstract

In this project we explore the presence of ambiguity in textual and visual media and its influence on accurately understanding and
capturing bias in news. We study this topic in the context of supporting
media scholars and social scientists in their media analysis. Our focus
lies on racial and gender bias as well as framing and the comparison
of their manifestation across modalities, cultures and languages. In this
paper we lay out a human in the loop approach to investigate the role of
ambiguity in detection and interpretation of bias.

Files

Paper4.pdf
(.pdf | 0.4 Mb)