5 papers
Echoes in the Sky: Computational Thematic Analysis of Online Public Discourse on Bluesky Across Trump's Reelection
Qile Wang, Ali Salloum, Carolina Coimbra Vieira +4
As political disruption intensifies online discourse, Bluesky has become an important platform for political discussion and public reaction. In this study, we examine large-scale d…
"The explanation makes sense": An Empirical Study on LLM Performance in News Classification and its Influence on Judgment in Human-AI Collaborative Annotation
Qile Wang, Prerana Khatiwada, Avinash Chouhan +5
The spread of media bias is a significant concern as political discourse shapes beliefs and opinions. Addressing this challenge computationally requires improved methods for interp…
Wisdom of the LLM Crowd: A Large Scale Benchmark of Multi-Label U.S. Election-Related Harmful Social Media Content
Qile Wang, Prerana Khatiwada, Carolina Coimbra Vieira +3
The spread of election misinformation and harmful political content conveys misleading narratives and poses a serious threat to democratic integrity. Detecting harmful content at e…
MalVis: A Large-Scale Image-Based Framework and Dataset for Advancing Android Malware Classification
Saleh J. Makkawy, Michael J. De Lucia, Kenneth E. Barner
As technology advances, Android malware continues to pose significant threats to devices and sensitive data. The open-source nature of the Android OS and the availability of its SD…
GReAT: A Graph Regularized Adversarial Training Method
Samet Bayram, Kenneth Barner
This paper presents GReAT (Graph Regularized Adversarial Training), a novel regularization method designed to enhance the robust classification performance of deep learning models.…