Semantic Network Analysis (SemNA): A Tutorial on Preprocessing, Estimating, and Analyzing Semantic Networks

Alexander P. Christensen, Yoed N. Kenett

Research output: Contribution to journalArticlepeer-review

29 Scopus citations

Abstract

To date, the application of semantic network methodologies to study cognitive processes in psychological phenomena has been limited in scope. One barrier to broader application is the lack of resources for researchers unfamiliar with the approach. Another barrier, for both the unfamiliar and knowledgeable researcher, is the tedious and laborious preprocessing of semantic data. We aim to minimize these barriers by offering a comprehensive semantic network analysis pipeline (preprocessing, estimating, and analyzing networks), and an associated R tutorial that uses a suite of R packages to accommodate the pipeline. Two of these packages, SemNetDictionaries and SemNetCleaner, promote an efficient, reproducible, and transparent approach to preprocessing linguistic data. The third package, SemNeT, provides methods and measures for estimating and statistically comparing semantic networks via a point-and-click graphical user interface. Using real-world data, we present a start-to-finish pipeline from raw data to semantic network analysis results. This article aims to provide resources for researchers, both the unfamiliar and knowledgeable, that reduce some of the barriers for conducting semantic network analysis.

Original languageEnglish
Pages (from-to)860-879
Number of pages20
JournalPsychological Methods
Volume28
Issue number4
Early online date23 Dec 2021
DOIs
StatePublished - Aug 2023
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2021 American Psychological Association

Keywords

  • network science
  • semantic memory
  • semantic networks
  • verbal fluency

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