Recommendation Systems

Today we will be discussing the possibilities and limitations of recommendation systems. This includes a consideration of how to balance the joy of ‘discovery’ and ‘fortuity’ (albiet instrumented) with the broader social and socio-political impacts of ‘leading’ users down a particular path.

Slides

• Recommendation Systems Discussion

Readings

Required

• Swearingen, Kirsten & Sinha, Rashmi. Beyond algorithms: An HCI perspective on recommender systems.
• Cosley, Dan, et al (2003). Is seeing believing? How recommender system interfaces affect users' opinions. SIGCHI.
• Ekstrand, et al. All The Cool Kids, How Do They Fit In?: Popularity and Demographic Biases in Recommender Evaluation and Effectiveness. FAT.

Optional

The following readings are recommended for additional context:

• Valdez, André; Ziefle, Martina; & Verbert, Katrien (2016). HCI for Recommender Systems: the Past, the Present and the Future.
• Nguyen, Tien et al. Exploring the Filter Bubble: The Effect of Using Recommender Systems on Content Diversity. GroupLens Research, UMN.
• Dacrema, Maurizio; Cremonesi, Paolo; & Jannach, Dietmar (2019). Are We Really Making Much Progress? A Worrying Analysis of Recent Neural Recommendation Approaches.
• . Intro to Recommendation Systems. Google.