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03640nam a2200553 4500 |
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|a 9783319727004
|9 978-3-319-72700-4
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|a 10.1007/978-3-319-72700-4
|2 doi
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|d GrThAP
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|a TK5102.9
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|a TA1637-1638
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|a TTBM
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|a 621.382
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|a Naderi, Babak.
|e author.
|4 aut
|4 http://id.loc.gov/vocabulary/relators/aut
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|a Motivation of Workers on Microtask Crowdsourcing Platforms
|h [electronic resource] /
|c by Babak Naderi.
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|a 1st ed. 2018.
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|a Cham :
|b Springer International Publishing :
|b Imprint: Springer,
|c 2018.
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|a XIV, 112 p. 42 illus., 8 illus. in color.
|b online resource.
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|a text
|b txt
|2 rdacontent
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|a computer
|b c
|2 rdamedia
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|a online resource
|b cr
|2 rdacarrier
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|a text file
|b PDF
|2 rda
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|a T-Labs Series in Telecommunication Services,
|x 2192-2810
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|a Introduction -- Theoretical Background on Motivation -- Who are Crowdworkers? -- How to Measure Motivation -- What Determines Task Selection Strategies? -- What Influences Workers' Performance? -- Conclusion and Outlook.
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|a This book studies the motivation of crowdworkers to find out how to attract more people and reach a higher quality of outcomes. The book first proposes a taxonomy for studying the motivation of crowdworkers including the potential influencing factors, different types of motivation, and possible consequences and outcomes related to the motivation. Next, the CWMS questionnaire, an instrument for measuring the underlying motivation of crowdworkers is developed. It considers different dimensions of motivation suggested by the Self-Determination Theory of motivation which is a well-established and empirically validated psychological theory used in various domains. This instrument can be used to study the effect of platform and user characteristics on the general motivation of crowdworkers. Later, the task-specific motivation of crowdworkers is studied in detail: Influencing factors are investigated, subjective methods for measuring them are evaluated, a model for predicting worker's decision on taking a task is proposed, the relative importance of different factors for two populations of crowdworkers is studied, and finally, a model for predicting the expected workload (as one of the major influencing factors) given the task design is proposed.
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|a Signal processing.
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|a Image processing.
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|a Speech processing systems.
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|a Application software.
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|a Social media.
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|a Signal, Image and Speech Processing.
|0 http://scigraph.springernature.com/things/product-market-codes/T24051
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|a Information Systems Applications (incl. Internet).
|0 http://scigraph.springernature.com/things/product-market-codes/I18040
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|a Social Media.
|0 http://scigraph.springernature.com/things/product-market-codes/412020
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|a SpringerLink (Online service)
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|t Springer eBooks
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|i Printed edition:
|z 9783319726991
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776 |
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|i Printed edition:
|z 9783319727011
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|i Printed edition:
|z 9783319891989
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|a T-Labs Series in Telecommunication Services,
|x 2192-2810
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|u https://doi.org/10.1007/978-3-319-72700-4
|z Full Text via HEAL-Link
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|a ZDB-2-ENG
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|a Engineering (Springer-11647)
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