Collaborative
indexing systems have
attracted anincreasing amount of
attention over the last
threeyears One
fundamental limitation to such a system isthe
uncontrolled nature of its vocabulary, as thisconsists of terms users freely choose to indexresources. As a result, the vocabulary can be poorlystructured, making it difficult to identifysignificant clusters of users, resources, or termsimportant for search or exploration features.Pre-defined terms are suggested to reduce thisuncontrolled vocabulary; these consolidate term usage if users adopt them. However, this suggestionhas not yet been proved. This work therefore focuseson an empirical study of the adoption of pre-definedterms. The model of pre-defined term adoption (MPTA)is formulated by applying technology acceptance and diffusion of innovation theories, as well asconstructs of social network analysis. MPTA is thenvalidated by one lab experiment with 172 Germanstudents, before being cross- validated by two web experiments with 254 German and 160English-speaking subjects. Results indicate thatpre-defined terms are appropriate for reducing theuncontrolled nature of the vocabulary..
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