Principal Component Analysis: A Tool for Identifying Web Document Characteristics Affecting Quality of Drug Information Websites

doi:10.7324/japs.2017.71101

Abstract

Highlights

Nowadays, looking through the Internet has turned into a typical device for people who wish to find out about their good beings and medical problems (Jansen and Spink, 2006)
principal component analysis (PCA) was applied to the data and the principal components were plotted and visualized structurally for detection the most important characteristics which related to the quality of drug information websites
Four attributes were chosen to be the factors which mostly influence quality status of drug information websites. These findings provide consumers and patients to observe the quality of sites that provide drug information as well as to support Web authors for improving the quality of drug information websites

Summary

Introduction

Nowadays, looking through the Internet has turned into a typical device for people who wish to find out about their good beings and medical problems (Jansen and Spink, 2006). In the past seventy-two percent of online users surfed for health and medical information which described of one kind or another such as serious conditions of drug or diseases, general information, or minor health problems (Fox and Duggan, 2013). The purpose of this study is to apply principal component analysis (PCA) technique for identifying Web document characteristics that affect the designing drug information websites in order to achieve information quality. PCA consolidates the majority of the variables in which there are interrelated into a smaller number of principal components (PCs) (Sratthaphut, et al, 2013). Those PCs are visualized structurally, while holding as much as possible of the variation exhibits in the data set

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Conclusion