Advertising Content and Consumer Engagement on Social Media: Evidence from Facebook

Working Papers

We describe the effect of social media advertising content on customer engagement using data from Facebook. We content-code 106,316 Facebook messages across 782 companies, using a combination of Amazon Mechanical Turk and Natural Language Processing algorithms.Read More

‘People Who Liked This Study Also Liked’: An Empirical Investigation of the Impact of Recommender Systems on Sales Diversity

Working Papers

We investigate the impact of several different recommender algorithms (e.g.,’s “Consumers who bought this item also bought”), commonly used in ecommerce and online services, on sales volume and diversity, using field experiment data on movie sales from a top retailer in North America. Read More

Will the Global Village Fracture into Tribes: Recommender Systems and Their Effects on Consumers

Published Research

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.Read More