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Adrian Dale - Creatifica Associates
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JIS 35(3) Published

The June 2009 issue of the Journal of Information Science has been published.   I confess I had never heard of Peircean semiotics until this article from Huang was submitted: “Social tagging, online communication, and Peircean semiotics: a conceptual framework

JIS 35(1) Published

The February 2009 issue of the Journal of Information Science has been published.  An article by Nadine Hochstotter and Martina Koch Standard parameters for searching behaviour in search engines and their empirical evaluation introduces the concept of search “evergreens”.  Through an extended longitudinal study they showed that some search patterns in four major engines have stayed stable over a long period.

JIS 34(6) Published

The December 2008 issue of the Journal of Information Science has been published. An article by Dirk Lewandowski A three-year study on the freshness of web search engine databases has looked at the update frequency of the major web search engines:

The purpose is to analyse the update strategies of the major web search engines Google, Yahoo, and MSN/ We conducted a test of the updates of 40 daily updated pages and 30 irregularly updated pages. We used data from a time span of six weeks in the years 2005, 2006 and 2007. We found that the best search engine in terms of up-to-dateness changes over the years and that none of the engines has an ideal solution for index freshness. Indexing patterns are often irregular, and there seems to be no clear policy regarding when to revisit Web pages. A major problem identified in our research is the delay in making crawled pages available for searching, which differs from one engine to another.

JIS 34(5) Published

The October 2008 issue of the Journal of Information Science has been published. An article by Paul Huntington Web robot detection in the scholarly information environment has looked at the behaviour of web robots and identified that many now ignore the robots.txt protocol:

An increasing number of robots harvest information on the world wide web for a wide variety of purposes. Protocols developed at the inception of the web laid out voluntary procedures in order to identify robot behaviour, and exclude it if necessary. Few robots now follow this protocol and it is now increasingly difficult to filter for this activity in reports of on-site activity. This paper seeks to demonstrate the issues involved in identifying robots and assessing their impact on usage in regard to a project which sought to establish the relative usage patterns of open access and non-open access articles in the Oxford University Press published journal Glycobiology, which offers in a single issue articles in both forms. A number of methods for identifying robots are compared and together these methods found that 40% of the raw logs of this journal could be attributed to robots.