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lsemantica: A command for text similarity based on latent semantic analysis

Author

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  • Carlo Schwarz

    (University of Warwick)

Abstract

In this article, I present the lsemantica command, which implements latent semantic analysis in Stata. Latent semantic analysis is a machine learning algorithm for word and text similarity comparison and uses truncated singular value decomposition to derive the hidden semantic relationships between words and texts. lsemantica provides a simple command for latent semantic analysis as well as complementary commands for text similarity comparison.

Suggested Citation

  • Carlo Schwarz, 2019. "lsemantica: A command for text similarity based on latent semantic analysis," Stata Journal, StataCorp LP, vol. 19(1), pages 129-142, March.
    • Handle: RePEc:tsj:stataj:v:19:y:2019:i:1:p:129-142
    DOI: 10.1177/1536867X19830910
    Note: to access software from within Stata, net describe http://www.stata-journal.com/software/sj19-1/st0552/
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    Cited by:

    1. Callan Windsor, 2021. "The Intellectual Ideas Inside Central Banks: What'S Changed (Or Not) Since The Crisis?," Journal of Economic Surveys, Wiley Blackwell, vol. 35(2), pages 539-565, April.
    2. Rodet, Cortney S., 2022. "Does cognitive load affect creativity? An experiment using a divergent thinking task," Economics Letters, Elsevier, vol. 220(C).

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