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Presentation and response timing accuracy in Adobe Flash and HTML5/JavaScript Web experiments

Overview of attention for article published in Behavior Research Methods, June 2014
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (90th percentile)
  • High Attention Score compared to outputs of the same age and source (85th percentile)

Mentioned by

twitter
17 tweeters
q&a
1 Q&A thread

Citations

dimensions_citation
43 Dimensions

Readers on

mendeley
85 Mendeley
Title
Presentation and response timing accuracy in Adobe Flash and HTML5/JavaScript Web experiments
Published in
Behavior Research Methods, June 2014
DOI 10.3758/s13428-014-0471-1
Pubmed ID
Authors

Stian Reimers, Neil Stewart

Abstract

Web-based research is becoming ubiquitous in the behavioral sciences, facilitated by convenient, readily available participant pools and relatively straightforward ways of running experiments: most recently, through the development of the HTML5 standard. Although in most studies participants give untimed responses, there is a growing interest in being able to record response times online. Existing data on the accuracy and cross-machine variability of online timing measures are limited, and generally they have compared behavioral data gathered on the Web with similar data gathered in the lab. For this article, we took a more direct approach, examining two ways of running experiments online-Adobe Flash and HTML5 with CSS3 and JavaScript-across 19 different computer systems. We used specialist hardware to measure stimulus display durations and to generate precise response times to visual stimuli in order to assess measurement accuracy, examining effects of duration, browser, and system-to-system variability (such as across different Windows versions), as well as effects of processing power and graphics capability. We found that (a) Flash and JavaScript's presentation and response time measurement accuracy are similar; (b) within-system variability is generally small, even in low-powered machines under high load; (c) the variability of measured response times across systems is somewhat larger; and (d) browser type and system hardware appear to have relatively small effects on measured response times. Modeling of the effects of this technical variability suggests that for most within- and between-subjects experiments, Flash and JavaScript can both be used to accurately detect differences in response times across conditions. Concerns are, however, noted about using some correlational or longitudinal designs online.

Twitter Demographics

The data shown below were collected from the profiles of 17 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 85 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 6 7%
United States 3 4%
Mexico 2 2%
Iceland 1 1%
Australia 1 1%
Portugal 1 1%
Canada 1 1%
Colombia 1 1%
Unknown 69 81%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 24 28%
Researcher 16 19%
Professor 8 9%
Student > Master 7 8%
Unspecified 5 6%
Other 25 29%
Readers by discipline Count As %
Psychology 44 52%
Unspecified 12 14%
Computer Science 10 12%
Social Sciences 5 6%
Linguistics 5 6%
Other 9 11%

Attention Score in Context

This research output has an Altmetric Attention Score of 15. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 28 July 2019.
All research outputs
#1,059,751
of 13,327,820 outputs
Outputs from Behavior Research Methods
#106
of 1,148 outputs
Outputs of similar age
#17,660
of 190,428 outputs
Outputs of similar age from Behavior Research Methods
#2
of 14 outputs
Altmetric has tracked 13,327,820 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 92nd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,148 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.2. This one has done particularly well, scoring higher than 90% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 190,428 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 90% of its contemporaries.
We're also able to compare this research output to 14 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 85% of its contemporaries.