Popularity and findability through log analysis of search terms and queries: The case of a multilingual public service website

  • Ravid G
  • Bar-Ilan J
  • Baruchson-Arbib S
 et al. 
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Abstract

SHIL on the Web is the website of the Israeli Citizens Advice Bureau. It provides information about rights, social benefits, government and public services and civil obligations. Activity on the site approaches 10,000 pages visited per day. It has interfaces in four languages: Hebrew, Arabic, Russian and English. Logfile analy- sis of the SHIL website revealed to our surprise that about 60.7% of the requests reaching SHIL from external sites (excluding requests from robots) are from general search engines (e.g. Google and MSN), and users reach a specific page on the site linked from the search results page. This finding seems to indicate that the site is not known well enough to the public. On the other hand the site is very active, thus it seems to serve Israeli citizens well, even without being a well known brand. In this paper we analyzed the external requests coming from search engines. The analysis is based on the 266,295 queries from search engines that reached SHIL during MarchOctober 2005. Studying queries submitted to search engines is a novel technique for analyzing the access patterns to the site and provides a better understanding of the user needs and intentions than analyzing the dis- tribution of the visited pages only. We are not aware of any previous study that analyzed the relation between the query submitted to the search engine and the webpage the user clicked on the search results page. Since search engines provide snippets, when the user clicks on a specific page he already has some information on what is to be found on the page and the user makes a conscious decision to click on the specific result. Thus, this type of analysis provides additional information about the users actual information needs.

Author-supplied keywords

  • Information on public and governmental services and entitlements
  • Logfile analysis
  • Queries
  • Search engines

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