https://github.com/alexchristensen/semnet
Methods and Measures for Semantic Network Analysis
https://github.com/alexchristensen/semnet
r semantic-network-analysis
Last synced: about 1 year ago
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Methods and Measures for Semantic Network Analysis
- Host: GitHub
- URL: https://github.com/alexchristensen/semnet
- Owner: AlexChristensen
- Created: 2017-10-26T19:19:20.000Z (over 8 years ago)
- Default Branch: master
- Last Pushed: 2023-08-10T17:19:21.000Z (almost 3 years ago)
- Last Synced: 2023-10-25T13:38:08.670Z (over 2 years ago)
- Topics: r, semantic-network-analysis
- Language: R
- Homepage:
- Size: 2.14 MB
- Stars: 17
- Watchers: 4
- Forks: 4
- Open Issues: 3
-
Metadata Files:
- Readme: README.md
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README
### CRAN 1.4.3 | GitHub 1.4.4
[](https://www.repostatus.org/#active)[](https://cran.r-project.org/package=SemNeT) [](https://cran.r-project.org/package=SemNeT)
# How To Install
```
if(!"devtools" %in% row.names(installed.packages())){
install.packages("devtools")
}
devtools::install_github("AlexChristensen/SemNeT", dependencies = c("Imports", "Suggests"))
```
# How To Use
Christensen, A. P., & Kenett, Y. N. (in press). Semantic network analysis (SemNA): A tutorial on preprocessing, estimating, and analyzing semantic networks. *Psychological Methods*. https://doi.org/10.1037/met0000463 (see [PsyArXiv](https://psyarxiv.com/eht87/) for preprint)
# SemNeT
SemNeT offers researchers several tools for the analysis of their semantic network data. As a part of a module of semantic network packages, SemNeT is the most general, providing statistical analyses for all types of semantic networks.
## Forward Flow
Implements the forward flow measure introduced by Gray et al. (2019) and semantic spaces from Beaty et al. (2021).
## SemNeT Shiny
From raw data to semantic network analysis in three lines of code: The Shiny app allows for integration with [*SemNetCleaner*](https://github.com/AlexChristensen/SemNetCleaner), streamlining the SemNA pipeline:
```
# Grouping variable
group <- SemNeT::open.group
# Preprocessed data
clean <- SemNetCleaner::textcleaner(
data = SemNetCleaner::open.animals[,-c(1,2)], type = "fluency",
miss = 99, partBY = "row", dictionary = "animals"
)
# SemNeT Shiny app for network estimation and analyses
SemNeT::SemNeTShiny()
```
The point and click interface of the SemNeT Shiny app enables users to perform all analyses in the package as well as spreading activation analyses from the [*spreadr*](https://github.com/csqsiew/spreadr) package (Siew, 2019).
# References
Beaty, R. E., Zeitlen, D. C., Baker, B. S., & Kenett, Y. N. (2021).
Forward flow and creative thought: Assessing associative cognition and its role in divergent thinking.
*Thinking Skills and Creativity*, 100859. https://doi.org/10.1016/j.tsc.2021.100859
Christensen, A. P., Kenett, Y. N., Cotter, K. N., Beaty, R. E., & Silvia, P. J. (2018).
Remotely close associations: Openness to experience and semantic memory structure.
*European Journal of Personality*, *32*(4), 480-492. https://doi.org/10.1002/per.2157
Gray, K., Anderson, S., Chen, E. E., Kelly, J. M., Christian, M. S., Patrick, J., ... & Lewis, K. (2019).
“Forward flow”: A new measure to quantify free thought and predict creativity.
*American Psychologist*, *74*(5), 539-554. https://doi.org/10.1037/amp0000391
Kenett, Y. N., & Austerweil, J. L. (2016). Examining search processes in low and high creative individuals with random walks.
In *Paper presented at the proceedings of the 38th annual meeting of the cognitive sceince society* (pp. 313-318). Austin, TX. Retrieved from https://cogsci.mindmodeling.org/2016/papers/0066/index.html
Kenett, Y. N., Anaki, D., & Faust, M. (2014). Investigating the structure of semantic networks in low and high creative persons.
*Frontiers in Human Neuroscience*, *8*, 407. https://doi.org/10.3389/fnhum.2014.00407
Kenett, Y. N., Wechsler-Kashi, D., Kenett, D. Y., Schwartz, R. G., Ben Jacob, E., & Faust, M. (2013).
Semantic organization in children with cochlear implants: Computational analysis of verbal fluency.
*Frontiers in Psychology*, 4. https://doi.org/10.3389/fpsyg.2013.00543
Siew, C. S. Q. (2019).
spreadr: An R package to simulate spreading activation in a network.
*Behavior Research Methods*, *51*, 910-929. https://doi.org/10.3758/s13428-018-1186-5