14 citations · 50 across the 12 of their papers we have counts for
12 papers
The MovieLens Beliefs Dataset: Collecting Pre-Choice Data for Online Recommender Systems
Guy Aridor, Duarte Goncalves, Ruoyan Kong +2
An increasingly important aspect of designing recommender systems involves considering how recommendations will influence consumer choices. This paper addresses this issue by intro…
COVID-19 as Reflected in University President Bulk Email
Ruoyan Kong, Charles Chuankai Zhang, Jin Kang +2
E-mail ``Messages From the President'' to university students, staff, and faculty have long been used to keep campus communities aware of the latest policies, events, and news. But…
What Are We Optimizing For? A Human-centric Evaluation of Deep Learning-based Movie Recommenders
Ruixuan Sun, Xinyi Wu, Avinash Akella +3
In the past decade, deep learning (DL) models have gained prominence for their exceptional accuracy on benchmark datasets in recommender systems (RecSys). However, their evaluation…
Interactive Content Diversity and User Exploration in Online Movie Recommenders: A Field Experiment
Ruixuan Sun, Avinash Akella, Ruoyan Kong +2
Recommender systems often struggle to strike a balance between matching users' tastes and providing unexpected recommendations. When recommendations are too narrow and fail to cove…
Towards an Effective Organization-Wide Bulk Email System
Ruoyan Kong
Bulk email is widely used in organizations to communicate messages to employees. It is an important tool in making employees aware of policies, events, leadership updates, etc. How…
Organizational Bulk Email Systems: Their Role and Performance in Remote Work
Ruoyan Kong, Haiyi Zhu, Joseph A. Konstan
The COVID-19 pandemic has forced many employees to work from home. Organizational bulk emails now play a critical role to reach employees with central information in this work-from…
Less Can Be More: Exploring Population Rating Dispositions with Partitioned Models in Recommender Systems
Ruixuan Sun, Ruoyan Kong, Qiao Jin +1
In this study, we partition users by rating disposition - looking first at their percentage of negative ratings, and then at the general use of the rating scale. We hypothesize tha…
Getting the Most from Eye-Tracking: User-Interaction Based Reading Region Estimation Dataset and Models
Ruoyan Kong, Ruixuan Sun, Charles Chuankai Zhang +4
A single digital newsletter usually contains many messages (regions). Users' reading time spent on, and read level (skip/skim/read-in-detail) of each message is important for platf…
HierCat: Hierarchical Query Categorization from Weakly Supervised Data at Facebook Marketplace
Yunzhong He, Cong Zhang, Ruoyan Kong +5
Query categorization at customer-to-customer e-commerce platforms like Facebook Marketplace is challenging due to the vagueness of search intent, noise in real-world data, and imba…
Multi-Objective Personalization in Multi-Stakeholder Organizational Bulk E-mail: A Field Experiment
Ruoyan Kong, Chuankai Zhang, Ruixuan Sun +3
Bulk email is often used in organizations to communicate ``important-to-organization'' messages such as policy changes, organizational plans, and administrative updates. However, n…
The Informational Role of Online Recommendations: Evidence from a Field Experiment
Guy Aridor, Duarte Goncalves, Daniel Kluver +2
We conduct a field experiment on a movie-recommendation platform to investigate whether and how online recommendations influence consumption choices. Using a within-subjects design…
Learning to Ignore: A Case Study of Organization-Wide Bulk Email Effectiveness
Ruoyan Kong, Haiyi Zhu, Joseph A. Konstan
Bulk email is a primary communication channel within organizations, with all-company emails and regular newsletters serving as a mechanism for making employees aware of policies an…