20 citations · 21 across the 9 of their papers we have counts for
10 papers
AI Coding Agents in Social Science: Methodologically Diverse, Empirically Consistent, Interpretively Vulnerable
Meysam Alizadeh, Fabrizio Gilardi, Mohsen Mosleh +1
The deployment of LLM-based agents in scientific analysis raises opposing concerns: that agents may reduce methodological diversity, or that they may amplify the analytic flexibili…
AI Coding Agents Can Reproduce Social Science Findings
Meysam Alizadeh, Mohsen Mosleh, Fabrizio Gilardi +2
Recent anecdotal evidence suggests that AI coding agents can reproduce published findings when provided with original data and code; yet systematic evaluation across social science…
Unsupervised Elicitation of Moral Values from Language Models
Meysam Alizadeh, Fabrizio Gilardi, Zeynab Samei
As AI systems become pervasive, grounding their behavior in human values is critical. Prior work suggests that language models (LMs) exhibit limited inherent moral reasoning, leadi…
Web-Browsing LLMs Can Access Social Media Profiles and Infer User Demographics
Meysam Alizadeh, Fabrizio Gilardi, Zeynab Samei +1
Large language models (LLMs) have traditionally relied on static training data, limiting their knowledge to fixed snapshots. Recent advancements, however, have equipped LLMs with w…
Data marketplaces can increase the willingness to share social media data at low prices
Meysam Alizadeh, Fabrizio Gilardi
Living in the Post API age, researchers face unprecedented challenges in obtaining social media data, while users are concerned about how big tech companies use their data. Data do…
Societal AI Research Has Become Less Interdisciplinary
Dror Kris Markus, Fabrizio Gilardi, Daria Stetsenko
As artificial intelligence (AI) systems become deeply embedded in everyday life, calls to align AI development with ethical and societal values have intensified. Interdisciplinary…
Simple Prompt Injection Attacks Can Leak Personal Data Observed by LLM Agents During Task Execution
Meysam Alizadeh, Zeynab Samei, Daria Stetsenko +1
Previous benchmarks on prompt injection in large language models (LLMs) have primarily focused on generic tasks and attacks, offering limited insights into more complex threats lik…
Exploring Relationships Between Cryptocurrency News Outlets and Influencers' Twitter Activity and Market Prices
Meysam Alizadeh, Yasaman Asgari, Zeynab Samei +7
Academics increasingly acknowledge the predictive power of social media for a wide variety of events and, more specifically, for financial markets. Anecdotal and empirical findings…
Comparing Methods for Creating a National Random Sample of Twitter Users
Meysam Alizadeh, Darya Zare, Zeynab Samei +5
Twitter data has been widely used by researchers across various social and computer science disciplines. A common aim when working with Twitter data is the construction of a random…
Open-Source LLMs for Text Annotation: A Practical Guide for Model Setting and Fine-Tuning
Meysam Alizadeh, Maël Kubli, Zeynab Samei +5
This paper studies the performance of open-source Large Language Models (LLMs) in text classification tasks typical for political science research. By examining tasks like stance,…