Multidimensional News Quality: A Comparison of Crowdsourcing and Nichesourcing
Multidimensional News Quality: A Comparison of Crowdsourcing and Nichesourcing
In the age of fake news and of filter bubbles, assessing the quality of information is a compelling issue: it is important for users to understand the quality of the information they consume online. We report on our experiment aimed at understanding if workers from the crowd can be a suitable alternative to experts for information quality assessment. Results show that the data collected by crowdsourcing seem reliable. The agreement with the experts is not full, but in a task that is so complex and related to the assessor’s background, this is expected and, to some extent, positive.
Maddalena, Eddy
397dbaba-4363-4c11-8e52-4a7ba4df4bae
Ceolin, Davide
51d8eaac-ba0e-4c31-92f3-f42ae2608409
Mizzaro, Stefano
7be30144-afe5-42bb-a861-59a451decc20
22 October 2018
Maddalena, Eddy
397dbaba-4363-4c11-8e52-4a7ba4df4bae
Ceolin, Davide
51d8eaac-ba0e-4c31-92f3-f42ae2608409
Mizzaro, Stefano
7be30144-afe5-42bb-a861-59a451decc20
Maddalena, Eddy, Ceolin, Davide and Mizzaro, Stefano
(2018)
Multidimensional News Quality: A Comparison of Crowdsourcing and Nichesourcing.
In Proceedings of the 6th International Workshop on News Recommendation and Analytics (INRA 2018).
ACM.
4 pp
.
Record type:
Conference or Workshop Item
(Paper)
Abstract
In the age of fake news and of filter bubbles, assessing the quality of information is a compelling issue: it is important for users to understand the quality of the information they consume online. We report on our experiment aimed at understanding if workers from the crowd can be a suitable alternative to experts for information quality assessment. Results show that the data collected by crowdsourcing seem reliable. The agreement with the experts is not full, but in a task that is so complex and related to the assessor’s background, this is expected and, to some extent, positive.
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Published date: 22 October 2018
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Local EPrints ID: 427997
URI: http://eprints.soton.ac.uk/id/eprint/427997
PURE UUID: 7586a025-2b71-4b97-9bce-933002f19854
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Date deposited: 06 Feb 2019 17:30
Last modified: 29 Jan 2020 17:20
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Contributors
Author:
Davide Ceolin
Author:
Stefano Mizzaro
University divisions
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