spreadr: Simulating Spreading Activation in a Network
The notion of spreading activation is a prevalent metaphor in the cognitive sciences. This package provides the tools for cognitive scientists and psychologists to conduct computer simulations that implement spreading activation in a network representation. The algorithmic method implemented in 'spreadr' subroutines follows the approach described in Vitevitch, Ercal, and Adagarla (2011, Frontiers), who viewed activation as a fixed cognitive resource that could spread among nodes that were connected to each other via edges or connections (i.e., a network). See Vitevitch, M. S., Ercal, G., & Adagarla, B. (2011). Simulating retrieval from a highly clustered network: Implications for spoken word recognition. Frontiers in Psychology, 2, 369. <doi:10.3389/fpsyg.2011.00369> and Siew, C. S. Q. (2019). spreadr: A R package to simulate spreading activation in a network. Behavior Research Methods, 51, 910-929. <doi:10.3758/s13428-018-1186-5>.
Version: |
0.2.0 |
Depends: |
Rcpp (≥ 0.12.5), R (≥ 2.10) |
Imports: |
Matrix, assertthat, igraph, extrafont, ggplot2 |
LinkingTo: |
Rcpp |
Suggests: |
dplyr, fs, gganimate, ggraph, gifski, knitr, rmarkdown, testthat (≥ 3.0.0) |
Published: |
2021-05-11 |
DOI: |
10.32614/CRAN.package.spreadr |
Author: |
Cynthia Siew [aut, cre],
Dirk U. Wulff [ctb],
Ning Yuan Lee [ctb] |
Maintainer: |
Cynthia Siew <cynsiewsq at gmail.com> |
License: |
GPL-3 |
NeedsCompilation: |
yes |
Materials: |
NEWS |
CRAN checks: |
spreadr results |
Documentation:
Downloads:
Reverse dependencies:
Linking:
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