Word of Mouth Mobile Crowdsourcing: Increasing Awareness of Physical, Cyber, and Social Interactions
- Publisher:
- Institute of Electrical and Electronics Engineers
- Publication Type:
- Journal Article
- Citation:
- IEEE MultiMedia Magazine, 2017, 24, (4), pp. 26-37
- Issue Date:
- 2017-10-01
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| Filename | Description | Size | |||
|---|---|---|---|---|---|
| Word_of_Mouth_Mobile_Crowdsourcing_Increasing_Awareness_of_Physical_Cyber_and_Social_Interactions.pdf | 1.98 MB |
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By fully exploring various sensing capabilities and multiple wireless interfaces of mobile devices and integrating them with human power and intelligence, mobile crowdsourcing (MCS) is emerging as an effective paradigm for large-scale multimedia-related applications. However, most MCS schemes use a direct mode, in which crowdworkers passively or actively select tasks and contribute without interacting and collaborating with each other; such a mode can hamper some time-constrained crowdsourced tasks. This article explores a different approach: MCS based on word of mouth (WoM), in which crowdworkers, apart from executing tasks, exploit their mobile social networks and/or physical encounters to actively recruit other appropriate individuals to work on the task. The authors describe a WoM-based MCS architecture and typical applications, which they divide into Internet-scale and local scale. They then systematically summarize the main technical challenges, including crowdworker recruitment, incentive design, security and privacy, and data quality control, and they compare typical solutions. Finally, from a systems-level viewpoint, they discuss several practical issues that must be resolved. This article is part of a special issue on cybersecurity.
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