Virginia Tech: Research Institution — Prolific Citations Library

Browse 2 peer-reviewed papers from Virginia Tech spanning Computational Social Science, Human-Computer Interaction (HCI) (2025). Research powered by Prolific's high-quality participant data.

This page lists 2 peer-reviewed papers from researchers at Virginia Tech in the Prolific Citations Library, a curated collection of research powered by high-quality human data from Prolific.

Papers (2 of 2)

Impact of annotator demographics on sentiment dataset labeling

Authors: Y Ding, J You, TK Machulla, J Jacobs, P Sen

Year: 2025

Published in: Proceedings of the ..., 2022 - dl.acm.org

Institution: University of California Irvine, University of Florida, State University of New York at Buffalo, University of Waterloo, Virginia Tech

Research Area: Computational Social Science, Human-Computer Interaction (HCI), Sentiment Analysis

Discipline: Computational Social Science

Demographic differences among annotators significantly affect sentiment dataset labels, causing up to a 4.5% accuracy difference in sentiment prediction models.

Methods: Crowdsourced annotations from >1000 workers combined with demographic data; analysis of multimodal sentiment datasets and evaluation using machine learning models.

Key Findings: Impact of annotator demographics on sentiment labeling and its effect on model predictions.

DOI: https://doi.org/10.1145/3555632

Citations: 28

Sample Size: 1000
Factors Shaping Perceptions of AI Tools Among a Nationally Representative Sample of US Adults

Authors: B Katz, N Abdelgawad, D Friedberg, P Roberts, S Misra

Year: 2025

Published in: Innovation in Aging, 2025•pmc.ncbi.nlm.nih.gov

Institution: Virginia Tech

Research Area: Human–AI Interaction (HCI), Technology Perception

Discipline: Behavioral Science

Age significantly influences perceptions of generative AI tools, with older individuals perceiving more benefits and fewer risks compared to younger individuals; thinking dispositions also play a role.

Methods: A nationally representative survey of US adults conducted via the Prolific platform using various AI-relevant scales, including attitudes, risks, benefits, frequency of use, expertise, and literacy assessments.

Key Findings: Demographic factors, industry types, thinking dispositions, and attitudes toward generative AI tools, including risk and utility perceptions.

Citations: 1

Sample Size: 500