Diffusion of latent semantic analysis as a research tool: A social network analysis approach

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Latent semantic analysis (LSA) is a relatively new research tool with a wide range of applications in different fields ranging from discourse analysis to cognitive science, from information retrieval to machine learning and so on. In this paper, we chart the development and diffusion of LSA as a research tool using social network analysis (SNA) approach that reveals the social structure of a discipline in terms of collaboration among scientists. Using Thomson Reuters’ Web of Science (WoS), we identified 65 papers with “latent semantic analysis” in their titles and 250 papers in their topics (but not in titles) between 1990 and 2008. We then analyzed those papers using bibliometric and SNA techniques such as co-authorship and cluster analysis. It appears that as the emphasis moves from the research tool (LSA) itself to its applications in different fields, citations to papers with LSA in their titles tend to decrease. The productivity of authors fits Lotka's Law while the network of authors is quite loose. Networks of journals cited in papers with LSA in their titles and topics are well connected.

论文关键词:Latent semantic analysis,Social network analysis,Co-authorship analysis,Cluster analysis

论文评审过程:Received 23 August 2009, Revised 25 October 2009, Accepted 9 November 2009, Available online 4 January 2010.

论文官网地址:https://doi.org/10.1016/j.joi.2009.11.003