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Optimising crowdsourcing efficiency: Amplifying human computation with validation

Chamberlain, Jon and Kruschwitz, Udo and Poesio, Massimo (2018) 'Optimising crowdsourcing efficiency: Amplifying human computation with validation.' it - Information Technology, 60 (1). 41 - 49. ISSN 2196-7032

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Abstract

Crowdsourcing has revolutionised the way tasks can be completed but the process is frequently inefficient, costing practitioners time and money. This research investigates whether crowdsourcing can be optimised with a validation process, as measured by four criteria: quality; cost; noise; and speed. A validation model is described, simulated and tested on real data from an online crowdsourcing game to collect data about human language. Results show that by adding an agreement validation (or a like/upvote) step fewer annotations are required, noise and collection time are reduced and quality may be improved.

Item Type: Article
Uncontrolled Keywords: Crowdsourcing, Empirical studies in interaction design, Interactive games, Social networks, Natural language processing
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Faculty of Science and Health > Computer Science and Electronic Engineering, School of
Depositing User: Elements
Date Deposited: 14 Sep 2018 16:02
Last Modified: 25 Jun 2019 12:58
URI: http://repository.essex.ac.uk/id/eprint/21626

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