2 citations · 3 across the 7 of their papers we have counts for
7 papers
Contextual Bandits for Maximizing Stimulated Word-of-Mouth Rewards
Ahmed Sayeed Faruk, Elena Zheleva
Stimulated word-of-mouth is a strategy that promotes information sharing through prompts or incentives. Optimizing stimulated word-of-mouth through social networks requires identif…
Debiasing Message Passing to Mitigate Popularity Bias in GNN-based Collaborative Filtering
Md Aminul Islam, Ahmed Sayeed Faruk, Sourav Medya +1
Collaborative filtering (CF) models based on graph neural networks (GNNs) achieve strong performance in recommender systems by propagating user-item signals over interaction graphs…
Learning Peer Influence Probabilities with Linear Contextual Bandits
Ahmed Sayeed Faruk, Mohammad Shahverdikondori, Elena Zheleva
In networked environments, it is common for users to share recommendations about content, products, services, and possible courses of action. Whether these recommendations are acce…
Estimating Causal Effects in Networks with Cluster-Based Bandits
Ahmed Sayeed Faruk, Jason Sulskis, Elena Zheleva
The gold standard for estimating causal effects is randomized controlled trial (RCT) or A/B testing where a random group of individuals from a population of interest are given trea…
MOTIV: Visual Exploration of Moral Framing in Social Media
Andrew Wentzel, Lauren Levine, Vipul Dhariwal +6
We present a visual computing framework for analyzing moral rhetoric on social media around controversial topics. Using Moral Foundation Theory, we propose a methodology for decons…
Bridging or Breaking: Impact of Intergroup Interactions on Religious Polarization
Rochana Chaturvedi, Sugat Chaturvedi, Elena Zheleva
While exposure to diverse viewpoints may reduce polarization, it can also have a backfire effect and exacerbate polarization when the discussion is adversarial. Here, we examine th…
Leveraging heterogeneous spillover in maximizing contextual bandit rewards
Ahmed Sayeed Faruk, Elena Zheleva
Recommender systems relying on contextual multi-armed bandits continuously improve relevant item recommendations by taking into account the contextual information. The objective of…