most citedExcitements and Concerns in the Post-ChatGPT Era: Deciphering Public Perception of AI through Social Media Analysis

10 citations · 20 across the 6 of their papers we have counts for

collaborators

6 papers

cs.CL2024

Evolver: Chain-of-Evolution Prompting to Boost Large Multimodal Models for Hateful Meme Detection

Jinfa Huang, Jinsheng Pan, Zhongwei Wan +2

Recent advances show that two-stream approaches have achieved outstanding performance in hateful meme detection. However, hateful memes constantly evolve as new memes emerge by fus…

cs.CV2023★ 4 cited

GPT-4V(ision) as A Social Media Analysis Engine

Hanjia Lyu, Jinfa Huang, Daoan Zhang +6

Recent research has offered insights into the extraordinary capabilities of Large Multimodal Models (LMMs) in various general vision and language tasks. There is growing interest i…

cs.CL2023★ 2 cited

Understanding Divergent Framing of the Supreme Court Controversies: Social Media vs. News Outlets

Jinsheng Pan, Zichen Wang, Weihong Qi +2

Understanding the framing of political issues is of paramount importance as it significantly shapes how individuals perceive, interpret, and engage with these matters. While prior…

cs.SI2023★ 10 cited

Excitements and Concerns in the Post-ChatGPT Era: Deciphering Public Perception of AI through Social Media Analysis

Weihong Qi, Jinsheng Pan, Hanjia Lyu +1

As AI systems become increasingly prevalent in various aspects of daily life, gaining a comprehensive understanding of public perception towards these AI systems has become increas…

cs.CL2023★ 2 cited

Bias or Diversity? Unraveling Fine-Grained Thematic Discrepancy in U.S. News Headlines

Jinsheng Pan, Weihong Qi, Zichen Wang +2

There is a broad consensus that news media outlets incorporate ideological biases in their news articles. However, prior studies on measuring the discrepancies among media outlets…

cs.CL2023★ 2 cited

Computational Assessment of Hyperpartisanship in News Titles

Hanjia Lyu, Jinsheng Pan, Zichen Wang +1

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…