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Article published In: The Mental Lexicon
Vol. 13:3 (2018) ► pp.388–393

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Methodological and analytic considerations

Semantic neighbourhoods

There’s an app for that

 | University of Windsor
 | University of Windsor
 | University of Windsor
 | University of Windsor
Published online: 14 May 2019
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https://doi.org/10.1075/ml.18015.lut
Abstract
The contributions of semantic processing have come under increasing attention in recent years (Yap, M. J., Pexman, P. M., Wellsby, M., Hargreaves, I. S. & Huff, M. J. (2012). An abundance of riches: cross-task comparisons of semantic richness effects in visual word recognition. Frontiers in Human Neuroscience, 6, 72.Google Scholar logo with link to Google Scholar), and variables that measure the semantic content of words are a requirement of this increased experimental attention. The density and size of semantic neighborhoods derived from computational models have been shown to predict reaction times across a range of psycholinguistic tasks (e.g., Danguecan, A. N., & Buchanan, L. (2016). Semantic neighborhood effects for abstract versus concrete words. Frontiers in Psychology, 71, 1034. Google Scholar logo with link to Google Scholar), and the distance between two words in semantic space has been shown to predict priming (Kenett, Y. N., Levi, E., Anaki, D. & Faust, M. (2017). The semantic distance task: Quantifying semantic distance with semantic network path length. Journal of Experimental Psychology: Learning, Memory, and Cognition, 431, 1470–1489. Google Scholar logo with link to Google Scholar). The data to support the construction of stimulus sets that use these variables are complicated to obtain. The app that we describe here makes these measures of semantics available for 100,000 English words.
Article outline
  • Conclusion
  • References
References (14)
References
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