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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Tobias Kowatsch is interested in the adoption of mobile information systems at the Research Center for Intelligent Media in Furtwangen. He studied computer science in Germany and did social volunteering in South Africa. In 2006, he attended the Master's program Computer Science in Media at Furtwangen University and passed with distinction.
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