3 citations · 4 across the 5 of their papers we have counts for
6 papers
ValueGraph: Value-Signal Guided Graph Pre-training for Contextualized User Representation
Yitong Han, Wei Gao, Yi Zhao +3
Value signals are aggregated user-level moral representations that capture users' inferred value-related tendencies from their online discourse. User behavior on social media is sh…
Investigating the effectiveness of multimodal data in forecasting SARS-COV-2 case surges
Palur Venkata Raghuvamsi, Siyuan Brandon Loh, Prasanta Bhattacharya +4
The COVID-19 pandemic response relied heavily on statistical and machine learning models to predict key outcomes such as case prevalence and fatality rates. These predictions were…
Rethinking stance detection: A theoretically-informed research agenda for user-level inference using language models
Prasanta Bhattacharya, Hong Zhang, Yiming Cao +4
Stance detection has emerged as a popular task in natural language processing research, enabled largely by the abundance of target-specific social media data. While there has been…
Predicting User Stances from Target-Agnostic Information using Large Language Models
Siyuan Brandon Loh, Liang Ze Wong, Prasanta Bhattacharya +3
We investigate Large Language Models' (LLMs) ability to predict a user's stance on a target given a collection of his/her target-agnostic social media posts (i.e., user-level stanc…
From traces to measures: Large language models as a tool for psychological measurement from text
Joseph J. P. Simons, Wong Liang Ze, Prasanta Bhattacharya +2
Large language models are increasingly being used to label or rate psychological features in text data. This approach helps address one of the limiting factors of digital trace dat…
Enhancing Stance Classification on Social Media Using Quantified Moral Foundations
Hong Zhang, Quoc-Nam Nguyen, Prasanta Bhattacharya +5
This study enhances stance detection on social media by incorporating deeper psychological attributes, specifically individuals' moral foundations. These theoretically-derived dime…