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Please use this identifier to cite or link to this item:
http://hdl.handle.net/2451/29485
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| Title: | Recommender Systems and their Effects on Consumers: The Fragmentation Debate |
| Authors: | Fleder, Daniel - The Wharton School of the University of Pennsylvania
Hosanagar, Kartik - The Wharton School of the University of Pennsylvania
Buja, Andreas - The Wharton School of the University of Pennsylvania |
| Issue Date: | 2008 |
| Series/Report no.: | Net Institute Working Paper;08-44 |
| Abstract: | Recommender systems are becoming integral to how consumers discover
media. The value that recommenders offer is personalization: in
environments with many product choices, recommenders personalize the
browsing and consumption experience to each user's taste. Popular
applications include product recommendations at e-commerce sites and
online newspapers' automated selection of articles to display based on
the current reader's interests. This ability to focus more closely on
one's taste and filter all else out has spawned criticism that
recommenders will fragment consumers. Critics say recommenders cause
consumers to have less in common with one another and that the media
should do more to increase exposure to a variety of content. Others,
however, contend that recommenders do the opposite: they may homogenize
users because they share information among those who would otherwise not
communicate. These are opposing views, discussed in the literature for
over ten years for which there is not yet empirical evidence. We present
an empirical study of recommender systems in the music industry. In
contrast to concerns that users are becoming more fragmented, we find
that in our setting users become more similar to one another in their
purchases. This increase in similarity occurs for two reasons, which we
term volume and taste effects. The volume effect is that consumers
simply purchase more after recommendations, increasing the chance of
having more purchases in common. The taste effect is that, conditional
on volume, consumers buy a more similar mix of products after
recommendations. When we view consumers as a similarity network before
versus after recommendations, we find that the network becomes denser
and smaller, or characterized by shorter inter-user distances. These
findings suggest that for this setting, recommender systems are
associated with an increase in commonality among users and that concerns
of fragmentation may be misplaced. |
| URI: | http://hdl.handle.net/2451/29485 |
| Appears in Collections: | NET Institute Working Papers Series
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