Website entries from a web log file perspective : a new log file measure

Mayr, Philipp (2004) Website entries from a web log file perspective : a new log file measure. In Thelwall, Mike, Eds. Proceedings AoIR-ASIST 2004 Workshop on Web Science Research Methods, Brighton (UK).

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Abstract

Web log files record user transactions on webservers and offer due to their extent, their properties and potential an excellent investigation field for contemporary information and online behaviour studies [see also Nicholas et al., 1999]. Web log files actually offer the possibility to extract information about user access pattern, site visibility and site interlinking [see also Thelwall, 2001]. Furthermore web log file are excellent sources for informational investigations such as tracking spider behaviour, search engine query analysis or cognitive ergonomics. A drill down analysis to the smallest website entity (a specific web page) and also to other web entities, like directories or sites [see also Thelwall, 2003] can be performed with log data. This facilitates counting information usage frequencies on different levels of a website and enables new forms of information studies (e.g. finding regularities). Practical website insights for site access optimisation/evaluation are additional guaranteed.

Navigation on the web occurs in three separable types. The majority of online navigation is realized over hyperlinks which are set-up manually (e.g. directory entries, other intellectually build backlinks) or automatically (e.g. search engines, other web-based information systems). Direct navigation (e.g. over bookmarks, browser history) coexists between the “link-based” navigation and can be seen as an indication of well-known and perhaps authoritative websites. The three distinguishable web navigation types "navigation about search engine queries", "navigation about backlinks" and "direct navigation" can be separately identified in log data if the webserver provides the extended log file field “referer” [see also Thelwall, 2001].

Keywords:	Log file analysis, webometrics, metric
Subjects:	B. Information use and sociology of information. > BB. Bibliometric methods. C. Users, literacy and reading. > CA. Use studies.
ID Code:	2831
Deposited By:	Mayr, Philipp
Deposited On:	20 December 2004
Alternative Locations:	http://cybermetrics.wlv.ac.uk/AoIRASIST/mayr.html
All fields:	Show all fields

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