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Extracting and analyzing time-series HCI data from screen-captured task videos

Overview of attention for article published in Empirical Software Engineering, January 2016
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Mentioned by

facebook
1 Facebook page

Citations

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26 Dimensions

Readers on

mendeley
32 Mendeley
Title
Extracting and analyzing time-series HCI data from screen-captured task videos
Published in
Empirical Software Engineering, January 2016
DOI 10.1007/s10664-015-9417-1
Authors

Lingfeng Bao, Jing Li, Zhenchang Xing, Xinyu Wang, Xin Xia, Bo Zhou

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 32 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Denmark 1 3%
Belgium 1 3%
Unknown 30 94%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 12 38%
Student > Master 6 19%
Student > Bachelor 3 9%
Professor 2 6%
Other 1 3%
Other 3 9%
Unknown 5 16%
Readers by discipline Count As %
Computer Science 17 53%
Engineering 4 13%
Social Sciences 1 3%
Unknown 10 31%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 09 February 2017.
All research outputs
#20,403,545
of 22,953,506 outputs
Outputs from Empirical Software Engineering
#625
of 706 outputs
Outputs of similar age
#332,211
of 395,090 outputs
Outputs of similar age from Empirical Software Engineering
#6
of 11 outputs
Altmetric has tracked 22,953,506 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 706 research outputs from this source. They receive a mean Attention Score of 4.8. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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 395,090 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 11 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.