activity
20232025
most citedThe Parrot Dilemma: Human-Labeled vs. LLM-augmented Data in Classification Tasks

26 citations · 36 across the 5 of their papers we have counts for

collaborators

5 papers

cs.HC2025★ 1 cited

The Impact of Generative AI on Social Media: An Experimental Study

Anders Giovanni Møller, Daniel M. Romero, David Jurgens +1

Generative Artificial Intelligence (AI) tools are increasingly deployed across social media platforms, yet their implications for user behavior and experience remain understudied,…

cs.CL2024★ 2 cited

Real or Robotic? Assessing Whether LLMs Accurately Simulate Qualities of Human Responses in Dialogue

Jonathan Ivey, Shivani Kumar, Jiayu Liu +12

Studying and building datasets for dialogue tasks is both expensive and time-consuming due to the need to recruit, train, and collect data from study participants. In response, muc…

cs.CY2024

Prompt Refinement or Fine-tuning? Best Practices for using LLMs in Computational Social Science Tasks

Anders Giovanni Møller, Luca Maria Aiello

Large Language Models are expressive tools that enable complex tasks of text understanding within Computational Social Science. Their versatility, while beneficial, poses a barrier…

cs.CY2023★ 7 cited

The Persuasive Power of Large Language Models

Simon Martin Breum, Daniel Vædele Egdal, Victor Gram Mortensen +2

The increasing capability of Large Language Models to act as human-like social agents raises two important questions in the area of opinion dynamics. First, whether these agents ca…

cs.CL2023★ 26 cited

The Parrot Dilemma: Human-Labeled vs. LLM-augmented Data in Classification Tasks

Anders Giovanni Møller, Jacob Aarup Dalsgaard, Arianna Pera +1

In the realm of Computational Social Science (CSS), practitioners often navigate complex, low-resource domains and face the costly and time-intensive challenges of acquiring and an…