Oxford Internet Institute Papers

Browse 3 peer-reviewed papers from Oxford Internet Institute spanning Political Communication and Persuasion, Large Language Models (2024–2025). Research powered by Prolific's high-quality participant data.

This page lists 3 peer-reviewed papers from researchers at Oxford Internet Institute in the Prolific Citations Library, a curated collection of research powered by high-quality human data from Prolific.

Papers (3 of 3)

Comparing the persuasiveness of role-playing large language models and human experts on polarized US political issues

Authors: K Hackenburg, L Ibrahim, BM Tappin, M Tsakiris

Year: 2025

Published in: AI & SOCIETY, 2025 - Springer

Institution: Oxford Internet Institute, University of Oxford

Research Area: Political Communication and Persuasion, Large Language Models

Discipline: Political Science, Artificial Intelligence

GPT-4's ability to generate persuasive messages rivaled human experts on polarized US political issues, suggesting AI tools may have significant implications for political campaigns and democracy.

Methods: Pre-registered experiment where GPT-4 generated partisan role-playing persuasive messages, which were compared to those from human persuasion experts.

Key Findings: Persuasive impact of GPT-4-generated messages versus human expert messages on U.S. political issues.

Citations: 35

Sample Size: 4955
Why human-AI relationships need socioaffective alignment

Authors: HR Kirk, I Gabriel, C Summerfield, B Vidgen

Year: 2024

Published in: Humanities and Social ..., 2025 - nature.com

Institution: Oxford Internet Institute, University of Oxford

Research Area: Socioaffective Alignment in Human-AI Relationships, AI Ethics, Behavioral Science

Discipline: Artificial Intelligence, Behavioral Science

The paper emphasizes the need for socioaffective alignment in human-AI relationships to ensure AI systems support human psychological needs rather than exploit them, as interactions with AI transition from transactional to sustained engagement.

Methods: Conceptual analysis of socioaffective dynamics in human-AI interactions, framed through psychological theories and principles.

Key Findings: Exploration of how AI systems impact socioaffective relationships, psychological needs, autonomy, companionship, and human well-being.

DOI: https://doi.org/10.1057/s41599-025-04532-5

Citations: 59
The AI Community Building the Future? A Quantitative Analysis of Development Activity on Hugging Face Hub

Authors: HR Kirk, C Osborne

Year: 2024

Published in: ArXiv

Institution: Alan Turing Institute, Oxford Internet Institute, Oxford University

Research Area: Computational Social Science, AI Community Analysis, Hugging Face Hub Activity

Discipline: Computational Social Science