README.md

In AlexChristensen/SemNetToolbox: Methods and Measures for Semantic Network Analysis

CRAN 1.4.3 | GitHub 1.4.4

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 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, 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 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

AlexChristensen/SemNetToolbox documentation built on Aug. 20, 2023, 11:46 a.m.