73 citations · 129 across the 15 of their papers we have counts for
7 papers · 1 filter
Capturing Dynamics in Online Public Discourse: A Case Study of Universal Basic Income Discussions on Reddit
Rachel Kim, Veniamin Veselovsky, Ashton Anderson
Societal change is often driven by shifts in public opinion. As citizens evolve in their norms, beliefs, and values, public policies change too. While traditional opinion polling a…
Prevalence and prevention of large language model use in crowd work
Veniamin Veselovsky, Manoel Horta Ribeiro, Philip Cozzolino +3
We show that the use of large language models (LLMs) is prevalent among crowd workers, and that targeted mitigation strategies can significantly reduce, but not eliminate, LLM use.…
Tube2Vec: Social and Semantic Embeddings of YouTube Channels
Léopaul Boesinger, Manoel Horta Ribeiro, Veniamin Veselovsky +1
Research using YouTube data often explores social and semantic dimensions of channels and videos. Typically, analyses rely on laborious manual annotation of content and content cre…
Artificial Artificial Artificial Intelligence: Crowd Workers Widely Use Large Language Models for Text Production Tasks
Veniamin Veselovsky, Manoel Horta Ribeiro, Robert West
Large language models (LLMs) are remarkable data annotators. They can be used to generate high-fidelity supervised training data, as well as survey and experimental data. With the…
Generating Faithful Synthetic Data with Large Language Models: A Case Study in Computational Social Science
Veniamin Veselovsky, Manoel Horta Ribeiro, Akhil Arora +3
Large Language Models (LLMs) have democratized synthetic data generation, which in turn has the potential to simplify and broaden a wide gamut of NLP tasks. Here, we tackle a perva…
Reddit in the Time of COVID
Veniamin Veselovsky, Ashton Anderson
When the COVID-19 pandemic hit, much of life moved online. Platforms of all types reported surges of activity, and people remarked on the various important functions that online pl…
The Amplification Paradox in Recommender Systems
Manoel Horta Ribeiro, Veniamin Veselovsky, Robert West
Automated audits of recommender systems found that blindly following recommendations leads users to increasingly partisan, conspiratorial, or false content. At the same time, studi…