Latent Semantic Analysis: five methodological recommendations
Latent Semantic Analysis: five methodological recommendations
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DOI：
10.1057/ejis.2010.61
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发表时间：
2012-01-01
影响因子：
9.5
通讯作者：
Prybutok, Victor R.
中科院分区：
文献类型：
--
作者：
Evangelopoulos, Nicholas;Zhang, Xiaoni;Prybutok, Victor R.
最近文本数据的生成、存储和可用性的涌入给研究人员提出了开发合适的分析方法的挑战。潜在语义分析（LSA）是一系列方法方法中的一员，它通过将文本数据中的语义内容描述为一组向量，从而提供了解决这一差距的机会，由心理学、信息检索和文献计量学领域的研究人员首创。LSA涉及一种称为奇异值分解的矩阵运算，是主成分分析的一种扩展。LSA产生潜在的语义维度，如果研究人员的主要兴趣在于理解文本数据中的主题结构，那么这些维度要么是解释的，要么是用于聚类、分类和预测建模的目的，如果兴趣在于将原始文本转换为数字数据，作为后续分析的先驱。本文回顾了从事LSA研究的研究者需要解决的五个方法论问题。我们检查困境，提出的选择，并讨论考虑下，良好的方法决策作出。我们通过四项小型研究来说明这些问题，这些研究包括对发表在《欧洲信息系统杂志》上的论文摘要的分析。信息系统学报，2012,21,70-86。doi: 10.1057 / ejis.2010.61;2010年12月21日在线发布
The recent influx in generation, storage, and availability of textual data presents researchers with the challenge of developing suitable methods for their analysis. Latent Semantic Analysis (LSA), a member of a family of methodological approaches that offers an opportunity to address this gap by describing the semantic content in textual data as a set of vectors, was pioneered by researchers in psychology, information retrieval, and bibliometrics. LSA involves a matrix operation called singular value decomposition, an extension of principal component analysis. LSA generates latent semantic dimensions that are either interpreted, if the researcher's primary interest lies with the understanding of the thematic structure in the textual data, or used for purposes of clustering, categorization, and predictive modeling, if the interest lies with the conversion of raw text into numerical data, as a precursor to subsequent analysis. This paper reviews five methodological issues that need to be addressed by the researcher who will embark on LSA. We examine the dilemmas, present the choices, and discuss the considerations under which good methodological decisions are made. We illustrate these issues with the help of four small studies, involving the analysis of abstracts for papers published in the European Journal of Information Systems. European Journal of Information Systems (2012) 21, 70-86. doi:10.1057/ejis.2010.61; published online 21 December 2010