A Data-Driven Analysis of Workers' Earnings on Amazon Mechanical Turk

  title={A Data-Driven Analysis of Workers' Earnings on Amazon Mechanical Turk},
  author={Kotaro Hara and Abigail Adams and Kristy Milland and Saiph Savage and Chris Callison-Burch and Jeffrey P. Bigham},
  journal={Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems},
A growing number of people are working as part of on-line crowd work. [] Key Result Our analysis informs platform design and worker tools to create a more positive future for crowd work.

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Quantifying the Invisible Labor in Crowd Work

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Worker Demographics and Earnings on Amazon Mechanical Turk: An Exploratory Analysis

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Hourly Wages in Crowdworking: A Meta-Analysis

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Predicting the Working Time of Microtasks Based on Workers' Perception of Prediction Errors

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Striving to Earn More: A Survey of Work Strategies and Tool Use Among Crowd Workers

This work explored the strategies that both low and high-earning workers use to find and complete tasks via a survey of 360 workers on Amazon Mechanical Turk, finding many of the same tools and strategies in an attempt to earn more money, regardless of earning level.

Fair Work: Crowd Work Minimum Wage with One Line of Code

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Becoming the Super Turker:Increasing Wages via a Strategy from High Earning Workers

This paper explores how novice workers can improve their earnings by following the transparency criteria of Super Turkers, i.e., crowd workers who earn higher salaries on Amazon Mechanical Turk (MTurk), and highlights that tool development to support crowd workers should be paired with educational opportunities that teach workers how to effectively use the tools.

Becoming the Super Turker: Increasing Wages via a Strategy from High Earning Workers

This paper explores how novice workers can improve their earnings by following the transparency criteria of Super Turkers, i.e., crowd workers who earn higher salaries on Amazon Mechanical Turk (MTurk), and finds that novices who utilized this Super Turker criteria earned better wages than other novice.

Mechanical Turk and Financial Dependency on Crowdsourcing

This paper investigates whether workers who are financially dependent on income from Mechanical Turk produce work of different quality than workers who is not financially dependenton Mechanical Turk.



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More than fun and money. Worker Motivation in Crowdsourcing - A Study on Mechanical Turk

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Crowd-Workers: Aggregating Information Across Turkers to Help Them Find Higher Paying Work

A browser plugin that tracks the length of time it takes to complete a task, and a web service that aggregates the information across many workers that allows workers to discovery higher paying work by sorting tasks by estimated hourly rate.

Pay It Backward: Per-Task Payments on Crowdsourcing Platforms Reduce Productivity

Paid crowdsourcing marketplaces have gained popularity by using piecework, or payment for each microtask, to incentivize workers. This norm has remained relatively unchallenged. In this paper, we

A taxonomy of microtasks on the web

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The Dynamics of Micro-Task Crowdsourcing: The Case of Amazon MTurk

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Taking a HIT: Designing around Rejection, Mistrust, Risk, and Workers' Experiences in Amazon Mechanical Turk

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Examining Crowd Work and Gig Work Through the Historical Lens of Piecework

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Turk-Life in India

Previous studies on Amazon Mechanical Turk (AMT), the most well-known marketplace for microtasks, show that the largest population of workers on AMT is U.S. based, while the second largest is based