The information seeking behaviour of the users of digital scholarly journals

The article employs deep log analysis (DLA) techniques, a more sophisticated form of transaction log analysis, to demonstrate what usage data can disclose about information seeking behaviour of virtual scholars - academics, and researchers. DLA works with the raw server log data, not the processed, pre-defined and selective data provided by journal publishers. It can generate types of analysis that are not generally available via proprietary web logging software because the software filters out relevant data and makes unhelpful assumptions about the meaning of the data. DLA also enables usage data to be associated with search/navigational and/or user demographic data, hence the name 'deep'. In this connection the usage of two digital journal libraries, those of EmeraldInsight, and Blackwell Synergy are investigated. The information seeking behaviour of nearly three million users is analyzed in respect to the extent to which they penetrate the site, the number of visits made, as well as the type of items and content they view. The users are broken down by occupation, place of work, type of subscriber ("Big Deal", non-subscriber, etc.). geographical location, type of university (old and new), referrer link used, and number of items viewed in a session. (c) 2006 Elsevier Ltd. All rights reserved.