Collaboratively Adding Context to Social Media Posts Reduces the Sharing of False News
By Thomas Renault, David Restrepo - Amariles, Aurore Troussel - Clément
Rating
1323
Battle Count: 24
Relevance
3/10
While not directly related to quantitative trading, the methodology for analyzing information diffusion could be relevant for studying market sentiment and news impact
Implementation Complexity
6/10
Requires access to Twitter Pro API and implementation of difference-in-differences methodology
Reproducibility
4/5
The paper uses publicly available data from Twitter's Community Notes program and provides detailed methodology
About this paper
Methodology: Difference-in-Differences. Problem types: Causal Inference, Natural Language Processing.
The interactive Everscope explorer (charts, battles, favorites) loads below.