The primary goals of this research were to: 1) determine how amateur users of images in web environments self-categorize their interactions with images according to four proposed categories—information seeking, illustrative activity, social activity, or leisure, and; 2) identify which search strategies users rely on to find images online according to motivation.The sample consisted of 28 volunteers drawn from the School of Information Sciences. The study was conducted in a research lab in the University of Pittsburgh's Information Sciences building, where subjects were asked to complete a pre-questionnaire, five tasks using a web browser to locate and view images, and a post-questionnaire. They were also subsequently asked to complete a blog diary of their image retrieval activities over a period of three days. The data collected included pre- and post-questionnaires, video log transcripts, and diary data. The data was analyzed using quantitative analysis, descriptive statistics and probability values. Findings of the study show that: 1) information as a motivation is the overriding reason amateur users engage in image retrieval; 2) the other motivations vary in importance and are not always clearly delineated categories unto themselves, illuminating more about the various contexts of each motivation, and; 3) search strategy is relatively even across motivation. The research indicates that the context of the motivation may be shaped by whether an image is being sought purposefully (information and illustration) or less purposefully (social purposes and leisure) and whether it is being used as data or as an object, especially for information and illustration as motivations and to a lesser degree for social purposes and leisure. A spectrum of search strategy was uncovered ranging from illustration with the most directed, focused search strategy to leisure, the most undirected of motivations in terms of search strategy.A schematic was developed to illustrate the dynamic relationship between the motivations and their contexts. It offers a way of conceiving how the motivations appear on axes of purposeful versus less-than-purposeful image retrieval and data versus object. The schema will make an important contribution by charting what is an otherwise completely unknown area of image retrieval.
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