12 citations · 25 across the 5 of their papers we have counts for
6 papers
Debiasing International Attitudes: LLM Agents for Simulating US-China Perception Changes
Nicholas Sukiennik, Yichuan Xu, Yuqing Kan +4
Large Language Models (LLMs) offer transformative opportunities to address the longstanding challenge of modeling opinion evolution in computational social science. This study inve…
A Large-scale Dataset with Behavior, Attributes, and Content of Mobile Short-video Platform
Yu Shang, Chen Gao, Nian Li +1
Short-video platforms show an increasing impact on people's daily lives nowadays, with billions of active users spending plenty of time each day. The interactions between users and…
AgentSociety: Large-Scale Simulation of LLM-Driven Generative Agents Advances Understanding of Human Behaviors and Society
Jinghua Piao, Yuwei Yan, Jun Zhang +13
Understanding human behavior and society is a central focus in social sciences, with the rise of generative social science marking a significant paradigmatic shift. By leveraging b…
Modeling User Fatigue for Sequential Recommendation
Nian Li, Xin Ban, Cheng Ling +6
Recommender systems filter out information that meets user interests. However, users may be tired of the recommendations that are too similar to the content they have been exposed…
Uncovering the Deep Filter Bubble: Narrow Exposure in Short-Video Recommendation
Nicholas Sukiennik, Chen Gao, Nian Li
Filter bubbles have been studied extensively within the context of online content platforms due to their potential to cause undesirable outcomes such as user dissatisfaction or pol…
EconAgent: Large Language Model-Empowered Agents for Simulating Macroeconomic Activities
Nian Li, Chen Gao, Mingyu Li +2
The advent of artificial intelligence has led to a growing emphasis on data-driven modeling in macroeconomics, with agent-based modeling (ABM) emerging as a prominent bottom-up sim…