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Online content and products are presented as product networks, in which nodes are product pages linked by hyperlinks. These links are typically algorithmically induced recommendations based on aggregated data. Recently, websites have begun to offer social networks and user-generated links alongside the product network, creating a dual-network structure. The authors investigate the role of this dual-network structure in facilitating content exploration. They analyze YouTube's dual network and show that user pages have unique structural properties and act as content brokers. Next, the authors show that random rewiring of the product network cannot replicate this brokering effect. They present seven Internet studies in which participants browsing a YouTube-based website are exposed to different conditions of recommendations. The first set of studies shows that exposure to the dual network results in a more efficient (time to desirable outcome) and more effective (average product rating, overall satisfaction) exploration process. The next set of studies extends the previous ones to include dynamic structures, in which the network changes as a function of time or in response to participants' satisfaction. Furthermore, the results are replicated using data from another content site.
Goldenberg et al. (Wed,) studied this question.