Please use this identifier to cite or link to this item: https://dspace.iiti.ac.in/handle/123456789/4942
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dc.contributor.authorShrivastava, Abhisheken_US
dc.date.accessioned2022-03-17T01:00:00Z-
dc.date.accessioned2022-03-17T15:36:09Z-
dc.date.available2022-03-17T01:00:00Z-
dc.date.available2022-03-17T15:36:09Z-
dc.date.issued2018-
dc.identifier.citationAhmed, T., & Srivastava, A. (2018). Analyzing crowdsourcing to teach mobile crowdsensing a few lessons. Cognition, Technology and Work, 20(3), 457-475. doi:10.1007/s10111-018-0474-2en_US
dc.identifier.issn1435-5558-
dc.identifier.otherEID(2-s2.0-85044243253)-
dc.identifier.urihttps://doi.org/10.1007/s10111-018-0474-2-
dc.identifier.urihttps://dspace.iiti.ac.in/handle/123456789/4942-
dc.description.abstractIn recent years, mobile computing has shown so much potential that one can see a boundary-blurring expansion between the physical and the digital world. In this context, one of the most sought after research areas is mobile crowdsensing. To realize the vision of crowdsensing, there is a plethora of work in the literature that focuses on the technical capabilities of a mobile device. However, an important and a critical problem that eludes literature is the issue of human participation. We base this argument on a very simple, yet powerful fact that a mobile device is still a person’s private property. Therefore, considering human mentality, can we expect a person to contribute all the time? In this respect, it is not feasible for a human dependent computational system to ignore the inevitable human factor and focus only on the mechanical properties. In this paper, we look into the often ignored human aspects and will study the problem from a psychological perspective. We take inspiration from the mature paradigm of crowdsourcing and discuss the importance of a few human factors that could teach us how to encourage user participation in mobile crowdsensing. Further, we also explore a person’s habitual characteristics that could help answer the decade’s old question: How to get quality responses from the crowd? We use a psycho-technological approach to observe, understand, and find a few details regarding human behavior in online systems. Lastly, we take inspiration from the analysis to present a roadmap that aids in engineering a better and effective crowdsensing platform. © 2018, Springer-Verlag London Ltd., part of Springer Nature.en_US
dc.language.isoenen_US
dc.publisherSpringer Londonen_US
dc.sourceCognition, Technology and Worken_US
dc.subjectCrowdsourcingen_US
dc.subjectData miningen_US
dc.subjectHuman computer interactionen_US
dc.subjectHuman engineeringen_US
dc.subjectMobile devicesen_US
dc.subjectOnline systemsen_US
dc.subjectComputational systemen_US
dc.subjectComputer interactionen_US
dc.subjectCritical problemsen_US
dc.subjectCrowd sensingen_US
dc.subjectHuman behaviorsen_US
dc.subjectPrivate propertyen_US
dc.subjectTechnical capabilitiesen_US
dc.subjectUser participationen_US
dc.subjectBehavioral researchen_US
dc.titleAnalyzing crowdsourcing to teach mobile crowdsensing a few lessonsen_US
dc.typeJournal Articleen_US
Appears in Collections:Department of Computer Science and Engineering

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