Abstract
This study offers empirical evidence of Mix-of-Attributes (MOA) approach's analytical benefits, and illustrates how the MOA approach can be utilized. The study begins by content analyzing the most popular Web sites containing political user-generated content (UGC) and documenting presence of search efficiency, customizability, manipulability, participation cost reduction, and community orientation technological attributes. A cluster analysis is then used to develop classification of political UGC Web sites based on their attribute scores. The conventional and the attribute-based classifications of UGC are shown to be different, providing evidence of the MOA approach's usefulness. Theory-building implications of the attributes, the attribute-based classification, and the MOA approach are discussed.
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