# Weak Supervision in Analysis of News: Application to Economic Policy Uncertainty

arXiv: https://arxiv.org/abs/2209.05383 · HTML: https://mlsanity.com/paper/2209.05383/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 21 of its 58 references that are in the map.
- First posted on arXiv 10 Aug 2022.

## Builds on (most cited first, 21 of 21)

- [Attention Is All You Need](https://mlsanity.com/paper/1706.03762/) (2017)
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- [Adam: A Method for Stochastic Optimization](https://mlsanity.com/paper/1412.6980/) (2014)
- [RoBERTa: A Robustly Optimized BERT Pretraining Approach](https://mlsanity.com/paper/1907.11692/) (2019)
- [BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension](https://mlsanity.com/paper/1910.13461/) (2019)
- [Neural Machine Translation by Jointly Learning to Align and Translate](https://mlsanity.com/paper/1409.0473/) (2014)
- [Longformer: The Long-Document Transformer](https://mlsanity.com/paper/2004.05150/) (2020)
- [XLNet: Generalized Autoregressive Pretraining for Language Understanding](https://mlsanity.com/paper/1906.08237/) (2019)
- [Big Bird: Transformers for Longer Sequences](https://mlsanity.com/paper/2007.14062/) (2020)
- [Generalizing from a Few Examples: A Survey on Few-Shot Learning](https://mlsanity.com/paper/1904.05046/) (2019)
- [Snorkel: Rapid Training Data Creation with Weak Supervision](https://mlsanity.com/paper/1711.10160/) (2017)
- [Meta-Learning: A Survey](https://mlsanity.com/paper/1810.03548/) (2018)
- [Data Programming: Creating Large Training Sets, Quickly](https://mlsanity.com/paper/1605.07723/) (2016)
- [An Introduction to Deep Reinforcement Learning](https://mlsanity.com/paper/1811.12560/) (2018)
- [Snorkel DryBell: A Case Study in Deploying Weak Supervision at Industrial Scale](https://mlsanity.com/paper/1812.00417/) (2018)
- [Spherical Text Embedding](https://mlsanity.com/paper/1911.01196/) (2019)
- [Recent advances in directional statistics](https://mlsanity.com/paper/2005.06889/) (2020)
- [Directional Statistics in Machine Learning: a Brief Review](https://mlsanity.com/paper/1605.00316/) (2016)
- [Uncertainty over Uncertainty: Investigating the Assumptions, Annotations, and Text Measurements of Economic Policy Uncertainty](https://mlsanity.com/paper/2010.04706/) (2020)
- [Medical device surveillance with electronic health records](https://mlsanity.com/paper/1904.07640/) (2019)
- [Deep Text Mining of Instagram Data Without Strong Supervision](https://mlsanity.com/paper/1909.10812/) (2019)

## Abstract (arXiv)

The need for timely data analysis for economic decisions has prompted most economists and policy makers to search for non-traditional supplementary sources of data. In that context, text data is being explored to enrich traditional data sources because it is easy to collect and highly abundant. Our work focuses on studying the potential of textual data, in particular news pieces, for measuring economic policy uncertainty (EPU). Economic policy uncertainty is defined as the public's inability to predict the outcomes of their decisions under new policies and future economic fundamentals. Quantifying EPU is of great importance to policy makers, economists, and investors since it influences their expectations about the future economic fundamentals with an impact on their policy, investment and saving decisions. Most of the previous work using news articles for measuring EPU are either manual or based on a simple keyword search. Our work proposes a machine learning based solution involving weak supervision to classify news articles with regards to economic policy uncertainty. Weak supervision is shown to be an efficient machine learning paradigm for applying machine learning models in low resource settings with no or scarce training sets, leveraging domain knowledge and heuristics. We further generated a weak supervision based EPU index that we used to conduct extensive econometric analysis along with the Irish macroeconomic indicators to validate whether our generated index foreshadows weaker macroeconomic performance