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CrowdLang: A Programming Language for the Systematic Exploration of Human Computation Systems


Minder, Patrick; Bernstein, Abraham (2012). CrowdLang: A Programming Language for the Systematic Exploration of Human Computation Systems. In: Fourth International Conference on Social Informatics (SocInfo 2012), Lausanne, 5 December 2012 - 7 December 2012.

Abstract

Human computation systems are often the result of extensive lengthy trial-and-error refinements. What we lack is an approach to systematically engineer solutions based on past successful patterns.In this paper we present the CrowdLang1 programming framework for engineering complex computation systems incorporating large crowds of networked humans and machines with a library of known interaction patterns. We evaluate CrowdLang by programming a German-to-English translation program incorporating machine translation and a monolingual crowd. The evaluation shows that CrowdLang is able to simply explore a large design space of possible problem-solving programs with the simple variation of the used abstractions. In an experiment involving 1918 different human actors, we show that the resulting translation program significantly outperforms a pure machine translation in terms of adequacy and fluency whilst translating more than 30 pages per hour and approximates the human-translated gold standard to 75%.

Abstract

Human computation systems are often the result of extensive lengthy trial-and-error refinements. What we lack is an approach to systematically engineer solutions based on past successful patterns.In this paper we present the CrowdLang1 programming framework for engineering complex computation systems incorporating large crowds of networked humans and machines with a library of known interaction patterns. We evaluate CrowdLang by programming a German-to-English translation program incorporating machine translation and a monolingual crowd. The evaluation shows that CrowdLang is able to simply explore a large design space of possible problem-solving programs with the simple variation of the used abstractions. In an experiment involving 1918 different human actors, we show that the resulting translation program significantly outperforms a pure machine translation in terms of adequacy and fluency whilst translating more than 30 pages per hour and approximates the human-translated gold standard to 75%.

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21 citations in Scopus®
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Additional indexing

Item Type:Conference or Workshop Item (Paper), refereed, original work
Communities & Collections:03 Faculty of Economics > Department of Informatics
Dewey Decimal Classification:000 Computer science, knowledge & systems
Uncontrolled Keywords:CrowdLang,ProgrammingLanguage,HumanComputation, Collective Intelligence, Crowdsourcing, Translation Software
Language:English
Event End Date:7 December 2012
Deposited On:08 Oct 2012 14:13
Last Modified:15 Aug 2017 00:11
Publisher:Springer
Other Identification Number:merlin-id:7322

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