145 citations · 186 across the 8 of their papers we have counts for
9 papers
Evaluating Brand Retrieval and Ranking in Large Language Model Recommendations
Edward Malthouse, Kun-Yu Lee, Jing Yang +2
Large language models (LLMs) are increasingly used for product recommendation, but evaluating their recommendations presents challenges that differ from conventional information re…
Large Language Model-driven Multi-Agent Simulation for News Diffusion Under Different Network Structures
Xinyi Li, Yu Xu, Yongfeng Zhang +1
The proliferation of fake news in the digital age has raised critical concerns, particularly regarding its impact on societal trust and democratic processes. Diverging from convent…
Large Language Model Agent for Fake News Detection
Xinyi Li, Yongfeng Zhang, Edward C. Malthouse
In the current digital era, the rapid spread of misinformation on online platforms presents significant challenges to societal well-being, public trust, and democratic processes, i…
Exploring Fine-tuning ChatGPT for News Recommendation
Xinyi Li, Yongfeng Zhang, Edward C Malthouse
News recommendation systems (RS) play a pivotal role in the current digital age, shaping how individuals access and engage with information. The fusion of natural language processi…
A Preliminary Study of ChatGPT on News Recommendation: Personalization, Provider Fairness, Fake News
Xinyi Li, Yongfeng Zhang, Edward C. Malthouse
Online news platforms commonly employ personalized news recommendation methods to assist users in discovering interesting articles, and many previous works have utilized language m…
PBNR: Prompt-based News Recommender System
Xinyi Li, Yongfeng Zhang, Edward C. Malthouse
Online news platforms often use personalized news recommendation methods to help users discover articles that align with their interests. These methods typically predict a matching…
Toward the Next Generation of News Recommender Systems
Himan Abdollahpouri, Edward Malthouse, Joseph Konstan +2
This paper proposes a vision and research agenda for the next generation of news recommender systems (RS), called the table d'hote approach. A table d'hote (translates as host's ta…
User-centered Evaluation of Popularity Bias in Recommender Systems
Himan Abdollahpouri, Masoud Mansoury, Robin Burke +2
Recommendation and ranking systems are known to suffer from popularity bias; the tendency of the algorithm to favor a few popular items while under-representing the majority of oth…
Understanding and Overcoming Biases in Customer Reviews
Georgios Askalidis, Edward C. Malthouse
Our paper contributes to the literature recommending approaches to make online reviews more credible and representative. We analyze data from four diverse major online retailers an…