Results 151 to 160 of about 34,982 (194)
Some of the next articles are maybe not open access.
Quality management on Amazon Mechanical Turk
Proceedings of the ACM SIGKDD Workshop on Human Computation, 2010Crowdsourcing services, such as Amazon Mechanical Turk, allow for easy distribution of small tasks to a large number of workers. Unfortunately, since manually verifying the quality of the submitted results is hard, malicious workers often take advantage of the verification difficulty and submit answers of low quality. Currently, most requesters rely on
Panagiotis G. Ipeirotis +2 more
openaire +1 more source
2012
One of the major challenges of ANLP research is the constant balancing act between the need for large samples, and the excessive time and monetary resources necessary for acquiring those samples. Amazon’s Mechanical Turk (MTurk) is a web-based data collection tool that has become a premier resource for researchers who are interested in optimizing their
Amber Chauncey Strain, Lucille M. Booker
openaire +1 more source
One of the major challenges of ANLP research is the constant balancing act between the need for large samples, and the excessive time and monetary resources necessary for acquiring those samples. Amazon’s Mechanical Turk (MTurk) is a web-based data collection tool that has become a premier resource for researchers who are interested in optimizing their
Amber Chauncey Strain, Lucille M. Booker
openaire +1 more source
Assessing Work–Asthma Interaction With Amazon Mechanical Turk
Journal of Occupational & Environmental Medicine, 2015To illustrate the utility of crowdsourcing for occupational health surveillance.Amazon Mechanical Turk was used to recruit and obtain information from employed persons with asthma, who answered questions about work-asthma interactions.Data collection from 60 subjects required only a few hours. Participants spent on average 7 minutes responding to seven
Philip, Harber, Gondy, Leroy
openaire +2 more sources
Screening Amazon’s Mechanical Turk for Adults With ADHD
Journal of Attention Disorders, 2015Objective: Researchers are increasingly using Amazon’s Mechanical Turk (MTurk; www.mturk.com ) to recruit study participants. However, the utility of MTurk for investigations of ADHD in adulthood is unknown. Method: A total of 6,526 MTurk workers (median age range = 26-35 years) completed an online screening survey assessing their diagnostic histories
Brian T, Wymbs, Anne E, Dawson
openaire +2 more sources
Measuring Social Preferences on Amazon Mechanical Turk
2017Social preferences are receiving increased attention in the social sciences, especially in behavioral economics and social psychology. From this arises the need to measure individuals’ social preferences in both the laboratory and in surveys of the broader population. The recently proposed SVO slider measure (Murphy et al.
Höglinger, Marc, Wehrli, Stefan
openaire +1 more source
Renewal and resurgence phenomena generalize to Amazon's Mechanical Turk
Journal of the Experimental Analysis of Behavior, 2020Amazon's Mechanical Turk (MTurk) is a crowdsourcing platform that provides researchers with the potential for obtaining behavioral data for very little cost. However, the extent to which the results of common behavioral phenomena found in basic, translational, and applied laboratories may be reproduced (as a first step towards prospective research) via
Théo P, Robinson, Michael E, Kelley
openaire +2 more sources
Amazon's Mechanical Turk: A Comment
Journal of Advertising, 2017Kees et al. (2017) provide evidence from a comparative study that supports the use of Mechanical Turk (MTurk) data in advertising research when compared to student samples and online panel data.
openaire +1 more source
Sentiment popularity - Amazon Mechanical Turk dataset
2015Dataset re-collected from an original dataset collected by Pang, B., and Lee, L. 2004. "A sentimental education: Sentiment analysis using subjectivity summarization based on minimum cuts". In Proceedings of the 42nd annual meeting on Association for Computational Linguistics.
VENANZI, MATTEO +3 more
openaire +2 more sources
Utility data annotation with Amazon Mechanical Turk
2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, 2008We show how to outsource data annotation to Amazon Mechanical Turk. Doing so has produced annotations in quite large numbers relatively cheaply. The quality is good, and can be checked and controlled. Annotations are produced quickly. We describe results for several different annotation problems.
Alexander Sorokin, David Forsyth
openaire +1 more source
Weather Sentiment - Amazon Mechanical Turk dataset
2015Dataset re-collected using Amazon Mechanical Turk from an original dataset provided by CrowdFlower as part of the 2013 Crowdsourcing at Scale shared task challenge. The dataset contains 6000 classifications of the sentiment of 300 tweets, with gold-standard sentiment labels, provided by 110 workers.
VENANZI, MATTEO +3 more
openaire +2 more sources