World-class research

Our research team brings academic rigor to Meedan’s projects and tools. Through partnerships with the Oxford Internet Institute, Birmingham City University, and the University of Connecticut, among others, we have contributed research and analysis to dozens of peer-reviewed articles in the fields of computer science and communications.

Information ecosystems

Fairness and bias in AI

Measuring what Matters: Construct Validity in Large Language Model Benchmarks

Information ecosystems

Fairness and bias in AI

Neural steering vectors reveal dose and exposure-dependent impacts of human-AI relationships

Information ecosystems

When Claims Evolve: Evaluating and Enhancing the Robustness of Embedding Models Against Misinformation Edits

Information ecosystems

HateDay: Insights from a Global Hate Speech Dataset Representative of a Day on Twitter

Information ecosystems

Lost in translation: using global fact-checks to measure multilingual misinformation prevalence, spread, and evolution

EPJ Data Science

Information ecosystems

Community Moderation and the New Epistemology of Fact Checking on Social Media

Fairness and bias in AI

Why human-AI relationships need socioaffective alignment

Nature Humanities and Social Sciences Communications

Fairness and bias in AI

Scaling language model size yields diminishing returns for single-message political persuasion

Information ecosystems

Scaling Crowdsourced Election Monitoring: Construction and Evaluation of Classification Models for Multilingual and Cross-Domain Classification Settings

Fairness and bias in AI

Multilingual != Multicultural: Evaluating Gaps Between Multilingual Capabilities and Cultural Alignment in LLMs

Beyond English: Evaluating Automated Measurement of Moral Foundations in Non-English Discourse with a Chinese Case Study

Fairness and bias in AI

The PRISM Alignment Dataset: What Participatory, Representative and Individualised Human Feedback Reveals About the Subjective and Multicultural Alignment of Large Language Models

NeurIPS 2024 (Best paper award)