The reflection of hierarchical cluster analysis of co-occurrence matrices in SPSS
ZHOU Qiuju1; LENG Fuhai1; LEYDESDORFF Loet2; Fuhai Leng (E-mail: lengfh@mail.las.ac.cn).
2015-06-27
Source PublicationChinese Journal of Library and Information Science
Volume8Issue:2Pages:11-24
AbstractPurpose: To discuss the problems arising from hierarchical cluster analysis of co-occurrence matrices in SPSS, and the corresponding solutions.

Design/methodology/approach: We design different methods of using the SPSS hierarchical clustering module for co-occurrence matrices in order to compare these methods. We offer the correct syntax to deactivate the similarity algorithm for clustering analysis within the hierarchical clustering module of SPSS.

Findings: When one inputs co-occurrence matrices into the data editor of the SPSS hierarchical clustering module without deactivating the embedded similarity algorithm, the program calculates similarity twice, and thus distorts and overestimates the degree of similarity.

Practical implications: We offer the correct syntax to block the similarity algorithm for clustering analysis in the SPSS hierarchical clustering module in the case of co-occurrence matrices. This syntax enables researchers to avoid obtaining incorrect results.
 
Originality/value: This paper presents a method of editing syntax to prevent the default use of a similarity algorithm for SPSS's hierarchical clustering module. This will help researchers, especially those from China, to properly implement the co-occurrence matrix when using SPSS for hierarchical cluster analysis, in order to provide more scientific and rational results.; Purpose: To discuss the problems arising from hierarchical cluster analysis of co-occurrence matrices in SPSS, and the corresponding solutions.

Design/methodology/approach: We design different methods of using the SPSS hierarchical clustering module for co-occurrence matrices in order to compare these methods. We offer the correct syntax to deactivate the similarity algorithm for clustering analysis within the hierarchical clustering module of SPSS.

Findings: When one inputs co-occurrence matrices into the data editor of the SPSS hierarchical clustering module without deactivating the embedded similarity algorithm, the program calculates similarity twice, and thus distorts and overestimates the degree of similarity.

Practical implications: We offer the correct syntax to block the similarity algorithm for clustering analysis in the SPSS hierarchical clustering module in the case of co-occurrence matrices. This syntax enables researchers to avoid obtaining incorrect results.
 
Originality/value: This paper presents a method of editing syntax to prevent the default use of a similarity algorithm for SPSS's hierarchical clustering module. This will help researchers, especially those from China, to properly implement the co-occurrence matrix when using SPSS for hierarchical cluster analysis, in order to provide more scientific and rational results.
SubtypeResearch Papers
KeywordCo-occurrence Matrices Hierarchical Cluster Analysis Spss Similarity Algorithm The Syntax Editor
Subject Area新闻学与传播学 ; 图书馆、情报与文献学
URL查看原文
Indexed By其他
Language英语
Document Type期刊论文
Identifierhttp://ir.las.ac.cn/handle/12502/7807
CollectionJournal of Data and Information Science_Chinese Journal of Library and Information Science-2015
Corresponding AuthorFuhai Leng (E-mail: lengfh@mail.las.ac.cn).
Affiliation1.National Science Library, Chinese Academy of Sciences, 100190 Beijing, China
2.University of Amsterdam, Amsterdam School of Communication Research (ASCoR), PO Box 15793, 1001 NG Amsterdam, the Netherlands
First Author Affilication中国科学院文献情报中心
Recommended Citation
GB/T 7714
ZHOU Qiuju,LENG Fuhai,LEYDESDORFF Loet,et al. The reflection of hierarchical cluster analysis of co-occurrence matrices in SPSS[J]. Chinese Journal of Library and Information Science,2015,8(2):11-24.
APA ZHOU Qiuju,LENG Fuhai,LEYDESDORFF Loet,&Fuhai Leng .(2015).The reflection of hierarchical cluster analysis of co-occurrence matrices in SPSS.Chinese Journal of Library and Information Science,8(2),11-24.
MLA ZHOU Qiuju,et al."The reflection of hierarchical cluster analysis of co-occurrence matrices in SPSS".Chinese Journal of Library and Information Science 8.2(2015):11-24.
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