This study seeks to identify and quantify biases in simulating political samples with Large
Language Models, specifically focusing on vote choice and public opinion. Using the GPT …

In recent years, large language models (LLMs) have been widely adopted in political
science tasks such as election prediction, sentiment analysis, policy impact assessment, and …

The growth of social media, characterized by its multimodal nature, has led to the
emergence of diverse phenomena and challenges, which calls for an effective approach to …

Predicting roll call votes through modeling political actors has emerged as a focus in
quantitative political science and computer science. Widely used embedding-based …

Abstract Large Language Models (LLMs) have revolutionized Natural Language Processing
(NLP) based applications including automated text generation, question answering …

Short-text Expansion plays a significant role in enhancing the quality, diversity, and
practicality of Short-text, helping users to more comprehensively understand the content …

Traditional sociological research often relies on human participation, which, though
effective, is expensive, challenging to scale, and with ethical concerns. Recent …

In the realm of personalized recommendation systems, accurately capturing user
preferences and item characteristics is important for delivering relevant and satisfying …

Large Language Models (LLMs) have attracted a lot of attention in various fields due to their
superior performance, aiming to train hundreds of millions or more parameters on large …