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Efficient n-gram analysis in R with cmscu

Overview of attention for article published in Behavior Research Methods, August 2016
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (59th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (63rd percentile)

Mentioned by

twitter
4 tweeters

Readers on

mendeley
15 Mendeley
Title
Efficient n-gram analysis in R with cmscu
Published in
Behavior Research Methods, August 2016
DOI 10.3758/s13428-016-0766-5
Pubmed ID
Authors

David W. Vinson, Jason K. Davis, Suzanne S. Sindi, Rick Dale

Abstract

We present a new R package, cmscu, which implements a Count-Min-Sketch with conservative updating (Cormode and Muthukrishnan Journal of Algorithms, 55(1), 58-75, 2005), and its application to n-gram analyses (Goyal et al. 2012). By writing the core implementation in C++ and exposing it to R via Rcpp, we are able to provide a memory-efficient, high-throughput, and easy-to-use library. As a proof of concept, we implemented the computationally challenging (Heafield et al. 2013) modified Kneser-Ney n-gram smoothing algorithm using cmscu as the querying engine. We then explore information density measures (Jaeger Cognitive Psychology, 61(1), 23-62, 2010) from n-gram frequencies (for n=2,3) derived from a corpus of over 2.2 million reviews provided by a Yelp, Inc. dataset. We demonstrate that these text data are at a scale beyond the reach of other more common, more general-purpose libraries available through CRAN. Using the cmscu library and the smoothing implementation, we find a positive relationship between review information density and reader review ratings. We end by highlighting the important use of new efficient tools to explore behavioral phenomena in large, relatively noisy data sets.

Twitter Demographics

The data shown below were collected from the profiles of 4 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 15 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Switzerland 1 7%
Unknown 14 93%

Demographic breakdown

Readers by professional status Count As %
Researcher 4 27%
Student > Ph. D. Student 3 20%
Unspecified 2 13%
Librarian 2 13%
Professor > Associate Professor 2 13%
Other 2 13%
Readers by discipline Count As %
Psychology 3 20%
Economics, Econometrics and Finance 3 20%
Unspecified 2 13%
Computer Science 2 13%
Agricultural and Biological Sciences 1 7%
Other 4 27%

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 02 September 2016.
All research outputs
#6,224,054
of 11,805,631 outputs
Outputs from Behavior Research Methods
#433
of 969 outputs
Outputs of similar age
#104,525
of 265,652 outputs
Outputs of similar age from Behavior Research Methods
#18
of 49 outputs
Altmetric has tracked 11,805,631 research outputs across all sources so far. This one is in the 46th percentile – i.e., 46% of other outputs scored the same or lower than it.
So far Altmetric has tracked 969 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.6. This one has gotten more attention than average, scoring higher than 54% 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 265,652 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 59% of its contemporaries.
We're also able to compare this research output to 49 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 63% of its contemporaries.