Users’ perceptions of the Web as revealed by transaction log analysis

Abstract

When information seekers use an information retrieval system their strategy is based, at least in part, on the perceptions they have formed about that environment. A random sample was gathered of more than 2,000 actual search queries submitted by users to one Web search engine, WebCrawler, in two separate capture sessions. The results suggest that a high proportion of users do not employ advanced search features, and those who do frequently misunderstand them. Furthermore, many users seem to have formed a model of the Web that imbues it with the intelligence found in a reference librarian, for example, but not a retrieval system. The linguistic structure of many queries resembles a typical human‐human communication model that is unlikely to produce satisfactory results in a human‐computer communication environment such as that offered currently by the Web. Design of more intuitive systems is dependent upon a more complete understanding of user behaviour at the intellectual and emotional as well as the technical levels.

Observation: A Complex Research Method

“…As a nonparticipant, length of time is similar to many quantitative studies. For example, in their respective transaction log analysis studies, Moukdad and Large (2001) collected data during two thirty-minute sessions in one day, while Davis (2004) collected data over a three-month period. In the other roles researchers might have to spend years in the fi eld.…”

Digital user behaviour of academicians in a conflict zone, Kashmir

“…Analysis of usage and user behaviour of such online systems can provide valuable information on user behaviour in particular and usage of electronic information in general. Furthermore, the findings can be used to improve the effectiveness of these electronic The current issue and full text archive of this journal is available at www.emeraldinsight.com/0033-0337.htm Digital user behaviour of academicians 127 systems and identify areas for improvement, ranging from user interface and functionality to documentation and product training (Ke et al, 2002).Though more of the stress is laid via different studies (Bernon, 2008;Ghaphery, 2005;Haddow, 2013;Kapoor, 2010;Mohamed and Hassan, 2008;Moukdad and Large, 2001;Nicholas, Huntington and Watkinson, 2005;Nicholas, Huntington and Jamali, 2008;Park and Lee, 2013;Thomas et al, 1993;Suseela, 2011;Yeadon, 2001;Yu and Apps, 2000;Yun et al, 2006) on the use and usability of academic databases via log analysis, but log analysis can also help us in understanding the influence of political scenario on the user behaviour in the academic settings. Analysing user behaviour is a way of investigating user thinking and cognitive processes when interacting with information retrieval systems.…”

Associating search and navigation behavior through log analysis

“…Several influential studies have been conducted, with the intention of understanding how users search the Web, through careful inspection of Web log data. A study by (Moukdad & Large, 2001) gathered more than 2,000 actual search queries submitted by users to WebCrawler. A query‐level analysis was performed that included the correct/incorrect use of modifiers, the number of individual terms in the query, and the linguistic structure of the keywords.…”

“…Log data has been used in conjunction with other types of user evaluation strategies including usability studies providing the core data for our analyses with the intention to investigate human–computer interactions, especially the various aspects of online information retrieval such as information search and navigation behavior. Research in this area comes from several different research groups, such as digital library groups (Cooper, 2001; Jones, Cunningham, & McNab, 1998), Web data mining groups (Borges & Levene, 1999; Cooley, Tan, & Srivastava, 1999; Spiliopoulou & Faulstich, 1998) and the general Web information retrieval community (Jansen, 2000; Moukdad & Large, 2001; Spink, Bateman, & Jansen, 1999). These research groups have investigated several subareas pertaining to online search and navigation activity such as (a) investigating searchers' performance (Mat‐Hassan & Levene, 2001; Rumpradit & Donnell, 1999; Su, 1992), (b) establishing a profile of an effective searcher (Fenichel, 1981; Hsieh‐Yee, 1993; Marchionini, 1989), (c) establishing users' searching characteristics (Jansen, 2000; Moukdad & Large, 2001; Silverstein, Henziger, Marais, & Moricz, 1999; Spink, Bateman, & Jansen, 1999), and (d) understanding users' navigation behavior (Borges & Levene, 1999; Cooley et al, 1999; Spiliopoulou & Faulstich, 1999).…”