Abstract
Bias is inevitable and inherent in any form of communication. News often appear biased to citizens with different political orientations, and understood differently by news media scholars and the broader public. In this paper we advocate the need for accurate methods for bias identification in video news item, to enable rich analytics capabilities in order to assist humanities media scholars and social political scientists. We propose to analyze biases that are typical in video news (including framing, gender and racial biases) by means of a human-in-the-loop approach that combines text and image analysis with human computation techniques.
| Language | English |
|---|---|
| Title of host publication | Joint Proceedings SAD 2018 and CrowdBias 2018 |
| Subtitle of host publication | Proceedings of the 1st Workshop on Subjectivity, Ambiguity and Disagreement in Crowdsourcing, and Short Paper Proceedings of the 1st Workshop on Disentangling the Relation Between Crowdsourcing and Bias Management (SAD 2018 and CrowdBias 2018) co-located the 6th AAAI Conference on Human Computation and Crowdsourcing (HCOMP 2018). Zürich, Switzerland, July 5, 2018 |
| Editors | Lora Aroyo, Anca Dumitrache |
| Publisher | CEUR-WS |
| Pages | 88-92 |
| Number of pages | 5 |
| Publication status | Published - 2018 |
| Event | 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 - Zurich, Switzerland Duration: 5 Jul 2018 → … |
Publication series
| Name | CEUR Workshop Proceedings |
|---|---|
| Publisher | CEUR Workshop Proceedings |
| Volume | 2276 |
| ISSN (Print) | 1613-0073 |
Conference
| Conference | 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 |
|---|---|
| Country | Switzerland |
| City | Zurich |
| Period | 5/07/18 → … |
Fingerprint
Keywords
- Bias detection
- bias in news video files
- crowdsourcing
- human computation
- human in the loop
- machine learning
Cite this
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A human in the loop approach to capture bias and support media scientists in news video analysis. / Mavridis, Panagiotis; De Jong, Markus; Aroyo, Lora; Bozzon, Alessandro; De Vos, Jesse; Oomen, Johan; Dimitrova, Antoaneta; Badenoch, Alec.
Joint Proceedings SAD 2018 and CrowdBias 2018: Proceedings of the 1st Workshop on Subjectivity, Ambiguity and Disagreement in Crowdsourcing, and Short Paper Proceedings of the 1st Workshop on Disentangling the Relation Between Crowdsourcing and Bias Management (SAD 2018 and CrowdBias 2018) co-located the 6th AAAI Conference on Human Computation and Crowdsourcing (HCOMP 2018). Zürich, Switzerland, July 5, 2018. ed. / Lora Aroyo; Anca Dumitrache. CEUR-WS, 2018. p. 88-92 (CEUR Workshop Proceedings; Vol. 2276).Research output: Chapter in Book / Report / Conference proceeding › Conference contribution › Academic › peer-review
TY - GEN
T1 - A human in the loop approach to capture bias and support media scientists in news video analysis
AU - Mavridis, Panagiotis
AU - De Jong, Markus
AU - Aroyo, Lora
AU - Bozzon, Alessandro
AU - De Vos, Jesse
AU - Oomen, Johan
AU - Dimitrova, Antoaneta
AU - Badenoch, Alec
PY - 2018
Y1 - 2018
N2 - Bias is inevitable and inherent in any form of communication. News often appear biased to citizens with different political orientations, and understood differently by news media scholars and the broader public. In this paper we advocate the need for accurate methods for bias identification in video news item, to enable rich analytics capabilities in order to assist humanities media scholars and social political scientists. We propose to analyze biases that are typical in video news (including framing, gender and racial biases) by means of a human-in-the-loop approach that combines text and image analysis with human computation techniques.
AB - Bias is inevitable and inherent in any form of communication. News often appear biased to citizens with different political orientations, and understood differently by news media scholars and the broader public. In this paper we advocate the need for accurate methods for bias identification in video news item, to enable rich analytics capabilities in order to assist humanities media scholars and social political scientists. We propose to analyze biases that are typical in video news (including framing, gender and racial biases) by means of a human-in-the-loop approach that combines text and image analysis with human computation techniques.
KW - Bias detection
KW - bias in news video files
KW - crowdsourcing
KW - human computation
KW - human in the loop
KW - machine learning
UR - http://www.scopus.com/inward/record.url?scp=85058945383&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85058945383&partnerID=8YFLogxK
M3 - Conference contribution
T3 - CEUR Workshop Proceedings
SP - 88
EP - 92
BT - Joint Proceedings SAD 2018 and CrowdBias 2018
A2 - Aroyo, Lora
A2 - Dumitrache, Anca
PB - CEUR-WS
ER -