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Analyzing crowdsourcing to teach mobile crowdsensing a few lessons

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Abstract

In 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.

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Notes

  1. http://StackOverflow.com/.

  2. https://www.facebook.com/groups/259068995911/.

  3. http://data.stackexchange.com/StackOverflow/query/new.

  4. www.cs.waikato.ac.nz/ml/weka.

  5. http://www.cs.cmu.edu/afs/cs/Web/Groups/AI/areas/nlp/corpora/names/.

  6. http://politeness.mpi-sws.org/.

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Authors and Affiliations

  1. Indian Institute of Technology Indore, Indore, India

    Tanveer Ahmed & Abhishek Srivastava

  2. Bennett University, Greater Noida, India

    Tanveer Ahmed

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  1. Tanveer Ahmed
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  2. Abhishek Srivastava
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Correspondence to Tanveer Ahmed.

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Ahmed, T., Srivastava, A. Analyzing crowdsourcing to teach mobile crowdsensing a few lessons. Cogn Tech Work 20, 457–475 (2018). https://doi.org/10.1007/s10111-018-0474-2

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