What usage statistics say about online user behaviour

1
What usage statistics say about online user
behaviour

• Philip Davis, Librarian
• Cornell University

Presented at the 5th Fiesole Collection
Development Retreat, Oxford University, July 24,
2003.
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What do these stats mean?
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Usage statistics do not tell us

• what is being downloaded
• who did the downloading
• why an article was downloaded
• how many individuals are responsible for the
  statistics

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Why we cant know everything

• Patron confidentiality
• Use IP address as a surrogate for user
• Some IPs represent aggregate users
• Library proxy server
• Public computers in libraries and labs
• Dial-in modem users
• Some IPs are assigned dynamically

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Results of two studies (ACS)

• Article downloads by IP address
• Previous studies have reported only aggregate use
  analysis
• How scientists find the articles they read
• Using referral URL data. The location from which
  users were referred to the ACS site.

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Most users download few articles
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from few journals
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The relationship is quadratic
Each point represents a user
N 1283
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In fact, its an inverse square law
x/y2
N 1283
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Population size may be estimated
Each point represents a journal
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Analysis of individual use illustrates

• Most users download few articles from few
  journals
• A small number of users have a very large effect
  on total downloads
• User population size may be estimated by total use

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Different paths to same destination
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Web page referrals
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Most users referred infrequently
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from few sources
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Yielding same inverse square law
Each point represents a user
N 1591
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In summary

• Scientists will use many different pathways to
  the same literature
• But use few and consistent methods of referral
• Underestimated the use of e-mail and bookmarking
  as a source of referral
• Underestimated bibliographic indexes
• Overestimated importance of library catalog

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Implications

• Libraries
• Develop redundant tools to facilitate access to
  literature

• Publishers
• Facilitate direct linking to article
• Adoptions of linking standards

Save the time of the reader -- S.R.
Ranganathan, from the Five Laws of Library Science
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• P. Davis and L. Solla. An IP-level analysis of
  usage statistics for electronic journals in
  chemistry Making inferences about user-behavior.
  JASIST 54(11), 2003 in press.
• P. Davis. Information seeking behavior of
  scientists a transaction log analysis of
  referral URLs. (in review, JASIST, June 19,
  2003).
• http//people.cornell.edu/pages/pmd8/