AI and Analytics for Business
Research Paper Series
The Quest for Content: How User-Generated Links Can Facilitate Online Exploration
Online content and products are presented as product networks, where 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. We investigate the role of this dual-network structure in facilitating content exploration.
We analyze YouTube’s dual network and show that user pages have unique structural properties and act as content brokers. Next, we show that random rewiring of the product network cannot replicate this brokering effect. We present seven internet studies in which participants, browsing a YouTube-based website, are exposed to different conditions of recommendations. Our first studies show 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. We extend those studies to include dynamic structures, in which the network changes as a function of time or in response to participants’ satisfaction. We replicate our results using data from another content site (Last.fm).
Keywords: UGC, networks, social networks, product networks, electronic commerce, recommender systems