@inproceedings{0b867edbdef34e798c8dd29c1dd9ec3e,
title = "CaptureBias: Supporting media scholars with ambiguity-aware bias representation for news videos",
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.",
keywords = "Ambiguity-aware bias representation, Bias detection, Bias in news video files, Crowdsourcing, Disagreement, Human in the loop, Machine learning",
author = "{De Jong}, Markus and Panagiotis Mavridis and Lora Aroyo and Alessandro Bozzon and {De Vos}, Jesse and Johan Oomen and Antoaneta Dimitrova and Alec Badenoch",
year = "2018",
language = "English",
series = "CEUR Workshop Proceedings",
publisher = "CEUR-WS",
pages = "32--40",
editor = "Lora Aroyo and {Dumitrache }, Anca",
booktitle = "Joint Proceedings SAD 2018 and CrowdBias 2018",
note = "1st Workshop on Subjectivity, Ambiguity and Disagreement in Crowdsourcing, and Short Paper 1st Workshop on Disentangling the Relation Between Crowdsourcing and Bias Management, SAD+CrowdBias 2018 ; Conference date: 05-07-2018",
}