SNAFU: The Semantic Network and Fluency Utility

Jeffrey C. Zemla, Kesong Cao, Kimberly D. Mueller, Joseph L. Austerweil

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

The verbal fluency task—listing words from a category or words that begin with a specific letter—is a common experimental paradigm that is used to diagnose memory impairments and to understand how we store and retrieve knowledge. Data from the verbal fluency task are analyzed in many different ways, often requiring manual coding that is time intensive and error-prone. Researchers have also used fluency data from groups or individuals to estimate semantic networks—latent representations of semantic memory that describe the relations between concepts—that further our understanding of how knowledge is encoded. However computational methods used to estimate networks are not standardized and can be difficult to implement, which has hindered widespread adoption. We present SNAFU: the Semantic Network and Fluency Utility, a tool for estimating networks from fluency data and automatizing traditional fluency analyses, including counting cluster switches and cluster sizes, intrusions, perseverations, and word frequencies. In this manuscript, we provide a primer on using the tool, illustrate its application by creating a semantic network for foods, and validate the tool by comparing results to trained human coders using multiple datasets.

Original languageEnglish (US)
Pages (from-to)1681-1699
Number of pages19
JournalBehavior Research Methods
Volume52
Issue number4
DOIs
StatePublished - Aug 1 2020
Externally publishedYes

Keywords

  • Memory retrieval
  • Methodology
  • Semantic networks
  • Verbal fluency

ASJC Scopus subject areas

  • Experimental and Cognitive Psychology
  • Developmental and Educational Psychology
  • Arts and Humanities (miscellaneous)
  • Psychology (miscellaneous)
  • Psychology(all)

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