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, and , promote an efficient, reproducible, and transparent approach to preprocessing linguistic data. The third package, , 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. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Download full-text PDF

Source
http://dx.doi.org/10.1037/met0000463DOI Listing

Publication Analysis

Top Keywords

semantic network
20
network analysis
16
semantic
8
preprocessing estimating
8
estimating analyzing
8
semantic networks
8
resources researchers
8
researchers unfamiliar
8
unfamiliar knowledgeable
8
analysis
4

Similar Publications

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!