Social Media & Recommender Systems

Through Web 2.0, internet users can communicate and interact with each other online using digital media and technologies. The goal of our research in this area is to gain new insights into consumer behavior by analyzing the influences of social interaction and its significance on the internet. We focus on examining behavior in social networks, the impact of user-generated content, and a combined analysis of network and behavioral data.

To assist customers in their purchasing decisions, online retailers offer recommendations generated by provider-based recommender systems on one hand. On the other hand, customer reviews are made available. Through an experiment, we analyze the extent to which different recommendations generated by recommender systems and customer reviews influence customer behavior. Our results show that customer reviews do not necessarily have a positive effect for the provider, as they can contradict each other. Positive customer reviews support the effectiveness of provider-based recommendation systems.