Understanding characteristics of user-generated content as a source of extracting user value

This study aims to identify and categorize the characteristics of user-generated content to obtain a profound understanding on the user data, and actively utilize the data in extracting user values. Based on literature review, characteristics of online reviews and photos on Social Network Services (SNS) were investigated to evaluate five categories for online reviews (interactive, imprecise, cultural, biased, and ambivalent), and four categories for SNS photos (affirmative, condensed, informative, and archival). These categories were reclassified on the three axes representing individual-social, explicit-implicit, and pleasant-unpleasant, which are well known dimensions of user-generated value. As a preliminary study, this categorization is expected to act as a stepping stone in understanding the user-generated content. It will also help Human-Computer Interaction researchers to select and use data consistent with the research purpose, and could be served as the indexes for measuring the characteristics of the data generated in social media and online websites.