Search Results for author:
Found 5 papers, 2 papers with code
GPT-4V(ision) as A Social Media Analysis Engine
Our investigation begins with a preliminary quantitative analysis for each task using existing benchmark datasets, followed by a careful review of the results and a selection of qualitative samples that illustrate GPT-4V's potential in understanding multimodal social media content.
Understanding Divergent Framing of the Supreme Court Controversies: Social Media vs. News Outlets
Understanding the framing of political issues is of paramount importance as it significantly shapes how individuals perceive, interpret, and engage with these matters.
NEOLAF, an LLM-powered neural-symbolic cognitive architecture
This paper presents the Never Ending Open Learning Adaptive Framework (NEOLAF), an integrated neural-symbolic cognitive architecture that models and constructs intelligent agents.
Bias or Diversity? Unraveling Fine-Grained Thematic Discrepancy in U.S. News Headlines
There is a broad consensus that news media outlets incorporate ideological biases in their news articles.
Computational Assessment of Hyperpartisanship in News Titles
We first adopt a human-guided machine learning framework to develop a new dataset for hyperpartisan news title detection with 2, 200 manually labeled and 1. 8 million machine-labeled titles that were posted from 2014 to the present by nine representative media organizations across three media bias groups - Left, Central, and Right in an active learning manner.
