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Full-Text Articles in Computer Engineering
Worker Demographics And Earnings On Amazon Mechanical Turk: An Exploratory Analysis, Kotaro Hara, Kristy Milland, Benjamin V. Hanrahan, Chris Callison-Burch, Abigail Adams, Saiph Savage, Jeffrey P. Bigham
Worker Demographics And Earnings On Amazon Mechanical Turk: An Exploratory Analysis, Kotaro Hara, Kristy Milland, Benjamin V. Hanrahan, Chris Callison-Burch, Abigail Adams, Saiph Savage, Jeffrey P. Bigham
Research Collection School Of Computing and Information Systems
Prior research reported that workers on Amazon Mechanical Turk (AMT) are underpaid, earning about $2/h. But the prior research did not investigate the difference in wage due to worker characteristics (e.g., country of residence). We present the first data-driven analysis on wage gap on AMT. Using work log data and demographic data collected via online survey, we analyse the gap in wage due to different factors. We show that there is indeed wage gap; for example, workers in the U.S. earn $3.01/h while those in India earn $1.41/h on average.
Smartphone Sensing Meets Transport Data: A Collaborative Framework For Transportation Service Analytics, Yu Lu, Archan Misra, Wen Sun, Huayu Wu
Smartphone Sensing Meets Transport Data: A Collaborative Framework For Transportation Service Analytics, Yu Lu, Archan Misra, Wen Sun, Huayu Wu
Research Collection School Of Computing and Information Systems
We advocate for and introduce TRANSense, a framework for urban transportation service analytics that combines participatory smartphone sensing data with city-scale transportation-related transactional data (taxis, trains etc.). Our work is driven by the observed limitations of using each data type in isolation: (a) commonly-used anonymous city-scale datasets (such as taxi bookings and GPS trajectories) provide insights into the aggregate behavior of transport infrastructure, but fail to reveal individual-specific transport experiences (e.g., wait times in taxi queues); while (b) mobile sensing data can capture individual-specific commuting-related activities, but suffers from accuracy and energy overhead challenges due to usage artefacts and lack …
Sew-Ing A Simple Endorsement Web To Incentivize Trustworthy Participatory Sensing, T. Luo, S. Kanhere, Hwee-Pink Tan
Sew-Ing A Simple Endorsement Web To Incentivize Trustworthy Participatory Sensing, T. Luo, S. Kanhere, Hwee-Pink Tan
Research Collection School Of Computing and Information Systems
Two crucial issues to the success of participatory sensing are (a) how to incentivize the large crowd of mobile users to participate and (b) how to ensure the sensing data to be trustworthy. While they are traditionally being studied separately in the literature, this paper proposes a Simple Endorsement Web (SEW) to address both issues in a synergistic manner. The key idea is (a) introducing a social concept called nepotism into participatory sensing, by linking mobile users into a social “web of participants” with endorsement relations, and (b) overlaying this network with investment-like economic implications. The social and economic layers …