Computational analysis of US Congressional speeches reveals a shift from evidence to intuition
By Segun T. Aroyehun, Almog Simchon, Fabio Carrella, Jana Lasser, Stephan Lewandowsky, David Garcia
Rating
1259
Battle Count: 136
Relevance
3/10
While not directly applicable to quantitative trading, the methodology for analyzing language trends could potentially be adapted for sentiment analysis in financial contexts.
Implementation Complexity
6/10
Requires expertise in NLP and time series analysis, but uses relatively standard techniques.
Reproducibility
4/5
The paper provides detailed methodology and data sources. Code and data are available in public repositories.
About this paper
Methodology: Computational text analysis. Problem types: Natural Language Processing, Time Series Analysis, Regression.
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