Hit count estimate variability for website-specific queries in search engines

Hit count estimate variability for website-specific queries in search engines PurposeThe purpose of this paper is to determine the effect of the chosen search engine results page (SERP) on the website-specific hit count estimation indicator.Design/methodology/approachA sample of 100 Spanish rare disease association websites is analysed, obtaining the website-specific hit count estimation for the first and last SERPs in two search engines (Google and Bing) at two different periods in time (2016 and 2017).FindingsIt has been empirically demonstrated that there are differences between the number of hits returned on the first and last SERP in both Google and Bing. These differences are significant when they exceed a threshold value on the first SERP.Research limitations/implicationsFuture studies considering other samples, more SERPs and generating different queries other than website page count (<site>) would be desirable to draw more general conclusions on the nature of quantitative data provided by general search engines.Practical implicationsSelecting a wrong SERP to calculate some metrics (in this case, website-specific hit count estimation) might provide misleading results, comparisons and performance rankings. The empirical data suggest that the first SERP captures the differences between websites better because it has a greater discriminating power and is more appropriate for webometric longitudinal studies.Social implicationsThe findings allow improving future quantitative webometric analyses based on website-specific hit count estimation metrics in general search engines.Originality/valueThe website-specific hit count estimation variability between SERPs has been empirically analysed, considering two different search engines (Google and Bing), a set of 100 websites focussed on a similar market (Spanish rare diseases associations), and two annual samples, making this study the most exhaustive on this issue to date. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Aslib Journal of Information Management Emerald Publishing

Hit count estimate variability for website-specific queries in search engines

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Publisher
Emerald Publishing
Copyright
Copyright © Emerald Group Publishing Limited
ISSN
2050-3806
DOI
10.1108/AJIM-10-2017-0226
Publisher site
See Article on Publisher Site

Abstract

PurposeThe purpose of this paper is to determine the effect of the chosen search engine results page (SERP) on the website-specific hit count estimation indicator.Design/methodology/approachA sample of 100 Spanish rare disease association websites is analysed, obtaining the website-specific hit count estimation for the first and last SERPs in two search engines (Google and Bing) at two different periods in time (2016 and 2017).FindingsIt has been empirically demonstrated that there are differences between the number of hits returned on the first and last SERP in both Google and Bing. These differences are significant when they exceed a threshold value on the first SERP.Research limitations/implicationsFuture studies considering other samples, more SERPs and generating different queries other than website page count (<site>) would be desirable to draw more general conclusions on the nature of quantitative data provided by general search engines.Practical implicationsSelecting a wrong SERP to calculate some metrics (in this case, website-specific hit count estimation) might provide misleading results, comparisons and performance rankings. The empirical data suggest that the first SERP captures the differences between websites better because it has a greater discriminating power and is more appropriate for webometric longitudinal studies.Social implicationsThe findings allow improving future quantitative webometric analyses based on website-specific hit count estimation metrics in general search engines.Originality/valueThe website-specific hit count estimation variability between SERPs has been empirically analysed, considering two different search engines (Google and Bing), a set of 100 websites focussed on a similar market (Spanish rare diseases associations), and two annual samples, making this study the most exhaustive on this issue to date.

Journal

Aslib Journal of Information ManagementEmerald Publishing

Published: Mar 19, 2018

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