Han Institute: Research Institution — Prolific Citations Library

Browse 2 peer-reviewed papers from Han Institute spanning Computation and Language, Advertising (2025). Research powered by Prolific's high-quality participant data.

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

Papers (2 of 2)

Large Language Models Are More Persuasive Than Incentivized Human Persuaders

Authors: P. Schoenegger, F. Salvi, J. Liu, X. Nan, R. Debnath, B. Fasolo, E. Leivada, G. Recchia, F. Günther, A. Zarifhonarvar, J. Kwon, Z. Ul Islam, M. Dehnert, D. Y. H. Lee, M. G. Reinecke, D. G. Kamper, M. Kobaş, A. Sandford, J. Kgomo, L. Hewitt, S. Kapoor, K. Oktar, E. E. Kucuk, B. Feng, C. R. Jones, I. Gainsburg, S. Olschewski, N. Heinzelmann, F. Cruz, B. M. Tappin, T. Ma, P. S. Park, R. Onyonka, A. Hjorth, P. Slattery, Q. Zeng, L. Finke, I. Grossmann, A. Salatiello, E. Karger

Year: 2025

Published in: arXiv preprint arXiv ..., 2025 - arxiv.org

Institution: London School of Economics and Political Science, University of Cambridge, University College London, Massachusetts Institute of Technology, University of Oxford, Modulo Research, Stanford University, Federal Reserve Bank of Chicago, ETH Zürich, University of Johannesburg

Research Area: Computation and Language

Discipline: Social Science, Artificial Intelligence

This paper compares a frontier LLM (Claude Sonnet 3.5) against incentivized human persuaders in a conversational quiz setting, finding that the AI's persuasion capabilities surpass those of humans with real-money bonuses tied to performance.

Citations: 16
LLM-Generated Ads: From Personalization Parity to Persuasion Superiority

Authors: E Meguellati, S Civelli, L Han, A Bernstein

Year: 2025

Published in: arXiv preprint arXiv ..., 2025 - arxiv.org

Institution: Oregon Health Sciences University, Oregon University of California, Irvine, Han Institute, NYU School of Law, Bernstein Research

Research Area: Advertising, Persuasion Strategies, Human-AI Interaction in Content Generation

Discipline: Artificial Intelligence

LLM-generated advertisements achieved parity with human-written ads in personalization and demonstrated superiority in persuasion using psychological principles, outperforming human ads even when AI-origin detection impacted results.

Methods: Two-part study: First examined LLM personalization based on personality traits; second tested psychological persuasion principles using universal messages across authority, consensus, cognition, and scarcity.

Key Findings: Effectiveness of LLM-generated ads in personalization and persuasive storytelling compared to human-created ads.

Sample Size: 1200