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arXiv · 1808.06080

CrowdTruth 2.0: Quality Metrics for Crowdsourcing with Disagreement

Anca Dumitrache·Oana Inel·Lora Aroyo·Benjamin Timmermans·Chris Welty
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Abstract

Typically crowdsourcing-based approaches to gather annotated data use inter-annotator agreement as a measure of quality. However, in many domains, there is ambiguity in the data, as well as a multitude of perspectives of the information examples. In this paper, we present ongoing work into the CrowdTruth metrics, that capture and interpret inter-annotator disagreement in crowdsourcing. The CrowdTruth metrics model the inter-dependency between the three main components of a crowdsourcing system -- worker, input data, and annotation. The goal of the metrics is to capture the degree of ambiguity in each of these three components. The metrics are available online at https://github.com/CrowdTruth/CrowdTruth-core .

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Anca Dumitrache, Oana Inel, Lora Aroyo, Benjamin Timmermans, Chris Welty. 2018-08-18. CrowdTruth 2.0: Quality Metrics for Crowdsourcing with Disagreement. https://arxiv.org/abs/1808.06080

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