Will the Global Village Fracture Into Tribes? Recommender Systems and Their Effects on Consumer Fragmentation

Abstract

Personalization is becoming ubiquitous on the World Wide Web. Such systems use statistical techniques to infer a customer's preferences and recommend content best suited to him (e.g., "Customers who liked this also liked…"). A debate has emerged as to whether personalization has drawbacks. By making the Web hyperspecific to our interests, does it fragment Internet users, reducing shared experiences and narrowing media consumption? We study whether personalization is in fact fragmenting the online population. Surprisingly, it does not appear to do so in our study. Personalization appears to be a tool that helps users widen their interests, which in turn creates commonality with others. This increase in commonality occurs for two reasons, which we term volume and product-mix effects. The volume effect is that consumers simply consume more after personalized recommendations, increasing the chance of having more items in common. The product-mix effect is that, conditional on volume, consumers buy a more similar mix of products after recommendations. AbstractPersonalization is becoming ubiquitous on the World Wide Web. Such systems use statistical techniques to infer a customer's preferences and recommend content best suited to him (e.g., "Customers who liked this also liked…"). A debate has emerged as to whether personalization has drawbacks. By making the web hyper-specific to our interests, does it fragment internet users, reducing shared experiences and narrowing media consumption? We study whether personalization is in fact fragmenting the online population. Surprisingly, it does not appear to do so in our study. Personalization appears to be a tool that helps users widen their interests, which in turn creates commonality with others. This increase in commonality occurs for two reasons, which we term volume and product mix effects. The volume effect is that consumers simply consume more after personalized recommendations, increasing the chance of having more items in common. The product mix effect is that, conditional on volume, consumers buy a more similar mix of products after recommendations.

An investigation of how the Australian brewing industry influence consumers on Twitter

“…The internet's tendency to split the market into consumer tribes is a key driver in such fragmentation (Hosanagar, Fleder, Lee, & Buja, 2014). This opens up the opportunity for 'specialised e-mavens' on social media in niche markets.…”

Big data and learning analytics: Singular or plural?

“…Concerns have also been raised that automated personalization in the online business context may result in increased insularity and fragmentation, leading users to more of the same rather than exposing them to new ideas and cultures beyond their existing interests and biases (Sunstein, 2007). Empirical evidence, however, suggests that personalization instead results in increased homogenization (Hosanagar, et al, 2013) -but by guiding a large number of people to a limited number of popular resources, rather than by increasing the range of resources and ideas that users are exposed to (Lee and Hosanagar, 2014). Similar concerns have been expressed regarding learning analytics, with even strong proponents of learning analytics noting that 'aligning and regulating performance and behavior of individual teachers or learners against a statistical norm without investigating the reasons for their divergence may strongly stifle innovation, individuality, creativity and experimentation' [24].…”

How Questions and Answers Shape Online Marketplaces: The Case of Amazon Answer

“…In this paper, we adopt the difference-indifferences approach, which has been used extensively to unveil the effect of online review elements on product sales [6,7,17]. It is also widely adopted to establish causal arguments in other contexts when endogeneity issues are present [33,34]. In addition, we also include product popularity as an interaction term in our model since prior works have shown its moderating effect on the impact of eWOM volume on sales [7].…”