Information seeking on the Web: An integrated model of browsing and searching

Abstract

This paper presents findings from a study of how knowledge workers use the Web to seek external information as part of their daily work. Thirty-four users from seven companies took part in the study. Participants were mainly IT specialists, managers, and research/marketing/consulting staff working in organizations that included a large utility company, a major bank, and a consulting firm. Participants answered a detailed questionnaire and were interviewed individually in order to understand their information needs and information seeking preferences. A custom-developed WebTracker software application was installed on each of their workplace PCs, and participants'Web-use activities were then recorded continuously during two-week periods. The WebTracker recorded how participants used the browser to seek information on the Web: it logged menu choices, button bar selections, and keystroke actions, allowing browsing and searching sequences to be reconstructed. In a second round of personal interviews, participants recalled critical incidents of using information from the Web.Data from the two interviews and the WebTracker logs constituted the database for analysis. Sixty-one significant episodes of information seeking were identified. A model was developed to describe the common repertoires of information seeking that were observed. On one axis of the model, episodes were plotted according to the four scanning modes identified by Aguilar (1967), Weick and Daft (1983): undirected viewing, conditioned viewing, informal search, and formal search. Each mode is characterized by its own information needs and information seeking strategies. On the other axis of the model, episodes were plotted according to the occurrence of one or more of the six categories of information seeking behaviors identified by Ellis (1989, 1990): starting, chaining, browsing, differentiating, monitoring, and extracting. The study suggests that a behavioral framework that relates motivations (Aguilar) and moves (Ellis) may be helpful in analyzing patterns of Web-based information seeking.

Serendipity within a Ubiquitous Computing Environment: A Case for Opportunistic Browsing

“…In contrast, active search and ongoing search both involve active acquisition of information relevant to the goal of the search. Other classifications of browsing behaviour were proposed by [10] and [4], but neither of these include forms of browsing that could be considered opportunistic.…”

On the Web at home: Information seeking and Web searching in the home environment

“…The increase in information available on the Web has affected information seeking behavior, demonstrating that Web resources have become integral to people's lives and work (Hsieh-Yee, 2001). However, most studies on Web information seeking behavior have focused on work roles such as those of scholars (Rieh & Belkin, 2000), librarians (Scull, Milewski, & Millen, 1999), information technology workers (Choo, Detlor, & Turnbull, 1999), college students (Hsieh-Yee, 1998), and high school students (Fidel et al, 1999). Little research has been done on the Web information seeking behavior of ordinary people in everyday life, with few exceptions (e.g., Hektor, 2001;Savolainen, 1999).…”

Suggestions for a research framework for South Africa: how can we learn from web information seeking/searching studies?

“…focusing on information seeking in context (ISIC), Kuhlthau and Vakkari (1999) stress the need for methodology leading to new approaches to research methods that address broader aspects of users' lives than formerly recognised: 'This is the early stage of what is developing into a significant body of research that holds the potential for making a major contribution to the knowledge base of information science.' Choo (200 I), Choo et al (1999Choo et al ( , 2000aChoo et al ( , 2000bChoo et al ( , 2000c and Wang et al (2000) have made some progress in contributing to such a theory. Choo and his associates have developed a behavioural model of web information seeking behaviour.…”