4 citations · 8 across the 7 of their papers we have counts for
7 papers
Comment-level Topic Drift Analysis in the Reddit Corpus
Steven Morse, Daniel Runfola, Trenton W. Ford
We present a novel application of embedding-based dynamic topic modeling techniques to detect and quantify topic drift at the comment level in a massive corpus. By leveraging pretr…
Simulating Teams with LLM Agents: Interactive 2D Environments for Studying Human-AI Dynamics
Mohammed Almutairi, Charles Chiang, Haoze Guo +9
Enabling users to create their own simulations offers a powerful way to study team dynamics and performance. We introduce VirTLab, a system that allows researchers and practitioner…
VirtLab: An AI-Powered System for Flexible, Customizable, and Large-scale Team Simulations
Mohammed Almutairi, Charles Chiang, Haoze Guo +9
Simulating how team members collaborate within complex environments using Agentic AI is a promising approach to explore hypotheses grounded in social science theories and study tea…
DAVIS: Planning Agent with Knowledge Graph-Powered Inner Monologue
Minh Pham Dinh, Munira Syed, Michael G Yankoski +1
Designing a generalist scientific agent capable of performing tasks in laboratory settings to assist researchers has become a key goal in recent Artificial Intelligence (AI) resear…
MEWS: Real-time Social Media Manipulation Detection and Analysis
Trenton W. Ford, William Theisen, Michael Yankoski +4
This article presents a beta-version of MEWS (Misinformation Early Warning System). It describes the various aspects of the ingestion, manipulation detection, and graphing algorith…
Competition Dynamics in the Meme Ecosystem
Trenton Ford, Rachel Krohn, Tim Weninger
The creation and sharing of memes is a common modality of online social interactions. The goal of the present work is to better understand the collective dynamics of memes in this…
The Infinity Mirror Test for Graph Models
Satyaki Sikdar, Daniel Gonzalez Cedre, Trenton W. Ford +1
Graph models, like other machine learning models, have implicit and explicit biases built-in, which often impact performance in nontrivial ways. The model's faithfulness is often m…