scholarly journals Testing the Waters: Behavior across Participant Pools

2021 ◽  
Vol 111 (2) ◽  
pp. 687-719
Author(s):  
Erik Snowberg ◽  
Leeat Yariv
Keyword(s):  
External Validity ◽  
Large Scale ◽  
Student Population ◽  
University Student ◽  
Mechanical Turk ◽  
Amazon Mechanical Turk ◽  
Lab Experiments ◽  
The Us ◽  
Small Set ◽  
Observer Effects

We leverage a large-scale incentivized survey eliciting behaviors from (almost) an entire undergraduate university student population, a representative sample of the US population, and Amazon Mechanical Turk (MTurk) to address concerns about the external validity of experiments with student participants. Behavior in the student population offers bounds on behaviors in other populations, and correlations between behaviors are similar across samples. Furthermore, non-student samples exhibit higher levels of noise. Adding historical lab participation data, we find a small set of attributes over which lab participants differ from non-lab participants. An additional set of lab experiments shows no evidence of observer effects. (JEL C83, D90, D91)

scholarly journals Learning to be selfish? A large-scale longitudinal analysis of Dictator games played on Amazon Mechanical Turk

2019 ◽  
Author(s):  
Antonio Alonso Arechar ◽  
David Gertler Rand
Keyword(s):  
Longitudinal Analysis ◽  
Large Scale ◽  
Dictator Game ◽  
Mechanical Turk ◽  
Amazon Mechanical Turk ◽  
Social Setting ◽  
Negative Effects ◽  
Dictator Games

We investigate whether experience playing the Dictator Game (DG) affects prosociality by aggregating data from 37 experiments run on Amazon Mechanical Turk over a six-year period. While prior evidence has shown a correlation between experience on Amazon Mechanical Turk and selfishness, it is unclear to what extent this is the result of selection versus learning. Examining a total of 27,266 decisions made by 17,791 unique individuals, our data shows evidence of significant negative effects of both selection and learning. First, people who participated in a greater total number of our experiments were more selfish, even in their first game – indicating that people who are more likely to select into our experiments are more selfish. Second, a given individual tends to transfer less money over successive experiments – indicating that experience with the DG leads to greater selfishness. These results provide clear evidence of learning even in this non-strategic social setting.

scholarly journals The Language Demographics of Amazon Mechanical Turk

2014 ◽  
Vol 2 ◽  
pp. 79-92 ◽  
Author(s):  
Ellie Pavlick ◽  
Matt Post ◽  
Ann Irvine ◽  
Dmitry Kachaev ◽  
Chris Callison-Burch
Keyword(s):  
Large Scale ◽  
Language Skills ◽  
Statistical Machine Translation ◽  
Mechanical Turk ◽  
Amazon Mechanical Turk ◽  
Indian Languages ◽  
Parallel Corpora ◽  
Bilingual Dictionaries ◽  
Bilingual Speakers ◽  
Translation Systems

We present a large scale study of the languages spoken by bilingual workers on Mechanical Turk (MTurk). We establish a methodology for determining the language skills of anonymous crowd workers that is more robust than simple surveying. We validate workers’ self-reported language skill claims by measuring their ability to correctly translate words, and by geolocating workers to see if they reside in countries where the languages are likely to be spoken. Rather than posting a one-off survey, we posted paid tasks consisting of 1,000 assignments to translate a total of 10,000 words in each of 100 languages. Our study ran for several months, and was highly visible on the MTurk crowdsourcing platform, increasing the chances that bilingual workers would complete it. Our study was useful both to create bilingual dictionaries and to act as census of the bilingual speakers on MTurk. We use this data to recommend languages with the largest speaker populations as good candidates for other researchers who want to develop crowdsourced, multilingual technologies. To further demonstrate the value of creating data via crowdsourcing, we hire workers to create bilingual parallel corpora in six Indian languages, and use them to train statistical machine translation systems.

scholarly journals Anomalous responses on Amazon Mechanical Turk: An Indian perspective

2021 ◽  
Vol 8 (2) ◽  
pp. 205316802110169
Author(s):  
William O’Brochta ◽  
Sunita Parikh
Keyword(s):  
United States ◽  
Data Quality ◽  
The United States ◽  
Self Report ◽  
Mechanical Turk ◽  
Amazon Mechanical Turk ◽  
Foreign Workers ◽  
Improve Data Quality ◽  
The Us ◽  
Indian Perspective

What can researchers do to address anomalous survey and experimental responses on Amazon Mechanical Turk (MTurk)? Much of the anomalous response problem has been traced to India, and several survey and technological techniques have been developed to detect foreign workers accessing US-specific surveys. We survey Indian MTurkers and find that 26% pass survey questions used to detect foreign workers, and 3% claim to be located in the United States. We show that restricting respondents to Master Workers and removing the US location requirement encourages Indian MTurkers to correctly self-report their location, helping to reduce anomalous responses among US respondents and to improve data quality. Based on these results, we outline key considerations for researchers seeking to maximize data quality while keeping costs low.

scholarly journals Optimizing Images for an E-Cigarette Messaging Campaign: Liking and Perceived Effectiveness

2021 ◽  
Vol 18 (24) ◽  
pp. 12989
Author(s):  
Elise M. Stevens ◽  
Brittney Keller-Hamilton ◽  
Darren Mays ◽  
Jennifer B. Unger ◽  
Olivia A. Wackowski ◽  
...  
Keyword(s):  
Image Features ◽  
Mechanical Turk ◽  
Amazon Mechanical Turk ◽  
Perceived Effectiveness ◽  
Warning Label ◽  
Warning Labels ◽  
The Us ◽  
Education Campaigns ◽  
Potential Impact ◽  
Reasons For Use

Introduction: Given the prevalence of electronic vapor product (EVP) use among young people in the US, there is a need for effective vaping education campaigns. This study tested 32 images for liking and perceived effectiveness (PE) to identify optimal images for a messaging campaign. Method: Images were selected from current campaigns, warning labels, and other images based on young adult reasons for use. Images were coded for the presence of (1) people, (2) vapor, (3) device, (4) color, and (5) similarity to warning label image. Young adults (n = 200) were recruited from the Amazon Mechanical Turk platform. Participants were randomly assigned to view and rate six of the 32 images on liking as well as PE, which measured the potential impact of the image to discourage vaping appeal and use. Results: Images containing vapor and/or a device or e-liquid were not well-liked but were perceived as effective in discouraging vaping (ps < 0.05). Images from warning labels were also not well-liked but were perceived as significantly more effective than those not from a warning (p < 0.01). Liking and effectiveness of features was similar for both EVP users and non-users. Discussion: Images with specific features were rated as less likable but rated as higher on PE. However, the consistency of image features rated as effective by EVP users and non-users supports the utility of similar imagery for vaping prevention and reduction efforts.

scholarly journals A positive effect of flowers rather than eye images in a large-scale, cross-cultural dictator game

2012 ◽  
Vol 279 (1742) ◽  
pp. 3556-3564 ◽  
Author(s):  
Nichola J. Raihani ◽  
Redouan Bshary
Keyword(s):  
Labour Market ◽  
Large Scale ◽  
Dictator Game ◽  
Social Cues ◽  
Cross Cultural ◽  
Systematic Variation ◽  
Mechanical Turk ◽  
Amazon Mechanical Turk ◽  
Cooperative Behaviour ◽  
Positive Effect

People often consider how their behaviour will be viewed by others, and may cooperate to avoid gaining a bad reputation. Sensitivity to reputation may be elicited by subtle social cues of being watched: previous studies have shown that people behave more cooperatively when they see images of eyes rather than control images. Here, we tested whether eye images enhance cooperation in a dictator game, using the online labour market Amazon Mechanical Turk (AMT). In contrast to our predictions and the results of most previous studies, dictators gave away more money when they saw images of flowers rather than eye images. Donations in response to eye images were not significantly different to donations under control treatments. Dictator donations varied significantly across cultures but there was no systematic variation in responses to different image types across cultures. Unlike most previous studies, players interacting via AMT may feel truly anonymous when making decisions and, as such, may not respond to subtle social cues of being watched. Nevertheless, dictators gave away similar amounts as in previous studies, so anonymity did not erase helpfulness. We suggest that eye images might only promote cooperative behaviour in relatively public settings and that people may ignore these cues when they know their behaviour is truly anonymous.

Predictability of fouling-potential of raw water for ultrafiltration membranes

2011 ◽  
Vol 11 (4) ◽  
pp. 481-489
Author(s):  
S. Krause ◽  
A. Obermayer
Keyword(s):  
Water Quality ◽  
Membrane Fouling ◽  
Large Scale ◽  
High Capacity ◽  
Raw Water ◽  
Ultrafiltration Membranes ◽  
Small Water ◽  
Lab Experiments ◽  
Flux Decline ◽  
Public Drinking Water

The public drinking water supply of southern Germany is characterized by a rather decentralized network. Due to the hydrogeological setting in these parts of Germany many of the small water works with an average capacity of 50 m3/h have to treat raw water extracted from karstic or cliffy aquifers. These raw waters tend to be contaminated with particles and pathogens acquired during snowmelt or after strong rainfalls. In the last decade ultrafiltration has become the technology of choice for the removal of the aforementioned contaminants. Flux decline caused by unanticipated membrane fouling is the main limitation for the application of ultrafiltration membranes. This paper describes how membrane fouling phenomena can be predicted by using a statistical approach based on data from large scale filtration systems in combination with field and lab experiments on raw water quality and membrane performance. The data defines water quality and respective fouling phenomena both in technical scale filtration plants and in lab experiments of eleven different raw waters. The method described here is more economically feasible for small water works when compared to typical pilot experiments that are used for high capacity water works.

scholarly journals Analysis of 220 Years of Floodplain Population Dynamics in the US at Different Spatial Scales

Water ◽  
2021 ◽  
Vol 13 (2) ◽  
pp. 141
Author(s):  
Firoza Akhter ◽  
Maurizio Mazzoleni ◽  
Luigia Brandimarte
Keyword(s):  
Population Dynamics ◽  
Large Scale ◽  
Spatial Scales ◽  
National Level ◽  
State Level ◽  
Economic Activities ◽  
Protection Measures ◽  
Management Planning ◽  
The Us ◽  
Over Time

In this study, we explore the long-term trends of floodplain population dynamics at different spatial scales in the contiguous United States (U.S.). We exploit different types of datasets from 1790–2010—i.e., decadal spatial distribution for the population density in the US, global floodplains dataset, large-scale data of flood occurrence and damage, and structural and nonstructural flood protection measures for the US. At the national level, we found that the population initially settled down within the floodplains and then spread across its territory over time. At the state level, we observed that flood damages and national protection measures might have contributed to a learning effect, which in turn, shaped the floodplain population dynamics over time. Finally, at the county level, other socio-economic factors such as local flood insurances, economic activities, and socio-political context may predominantly influence the dynamics. Our study shows that different influencing factors affect floodplain population dynamics at different spatial scales. These facts are crucial for a reliable development and implementation of flood risk management planning.

scholarly journals Evaluating extinction, renewal, and resurgence of operant behavior in humans with Amazon Mechanical Turk

2021 ◽  
Vol 74 ◽  
pp. 101728
Author(s):  
Carolyn M. Ritchey ◽  
Toshikazu Kuroda ◽  
Jillian M. Rung ◽  
Christopher A. Podlesnik
Keyword(s):  
Operant Behavior ◽  
Mechanical Turk ◽  
Amazon Mechanical Turk

scholarly journals Cities Exacerbate Climate Warming

Urban Science ◽  
2021 ◽  
Vol 5 (1) ◽  
pp. 27
Author(s):  
Lahouari Bounoua ◽  
Kurtis Thome ◽  
Joseph Nigro
Keyword(s):  
Surface Temperature ◽  
Land Surface ◽  
Large Scale ◽  
Climate Models ◽  
Warming Trend ◽  
Climate Mitigation ◽  
Temperature Changes ◽  
Surface Warming ◽  
The Us

Urbanization is a complex land transformation not explicitly resolved within large-scale climate models. Long-term timeseries of high-resolution satellite data are essential to characterize urbanization within land surface models and to assess its contribution to surface temperature changes. The potential for additional surface warming from urbanization-induced land use change is investigated and decoupled from that due to change in climate over the continental US using a decadal timescale. We show that, aggregated over the US, the summer mean urban-induced surface temperature increased by 0.15 °C, with a warming of 0.24 °C in cities built in vegetated areas and a cooling of 0.25 °C in cities built in non-vegetated arid areas. This temperature change is comparable in magnitude to the 0.13 °C/decade global warming trend observed over the last 50 years caused by increased CO2. We also show that the effect of urban-induced change on surface temperature is felt above and beyond that of the CO2 effect. Our results suggest that climate mitigation policies must consider urbanization feedback to put a limit on the worldwide mean temperature increase.

scholarly journals Solar Thermochemical Hydrogen Production in the USA

2021 ◽  
Vol 13 (14) ◽  
pp. 7804
Author(s):  
Christoph Falter ◽  
Andreas Sizmann
Keyword(s):  
Hydrogen Production ◽  
Large Scale ◽  
Low Cost ◽  
The United States ◽  
Solar Irradiation ◽  
Transport Sector ◽  
Fossil Energy ◽  
The Us ◽  
The Usa ◽  
Solar Thermochemical

Hydrogen produced from renewable energy has the potential to decarbonize parts of the transport sector and many other industries. For a sustainable replacement of fossil energy carriers, both the environmental and economic performance of its production are important. Here, the solar thermochemical hydrogen pathway is characterized with a techno-economic and life-cycle analysis. Assuming a further increase of conversion efficiency and a reduction of investment costs, it is found that hydrogen can be produced in the United States of America at costs of 2.1–3.2 EUR/kg (2.4–3.6 USD/kg) at specific greenhouse gas emissions of 1.4 kg CO2-eq/kg. A geographical potential analysis shows that a maximum of 8.4 × 1011 kg per year can be produced, which corresponds to about twelve times the current global and about 80 times the current US hydrogen production. The best locations are found in the Southwest of the US, which have a high solar irradiation and short distances to the sea, which is beneficial for access to desalinated water. Unlike for petrochemical products, the transport of hydrogen could potentially present an obstacle in terms of cost and emissions under unfavorable circumstances. Given a large-scale deployment, low-cost transport seems, however, feasible.

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