# Can LLMs Learn Macroeconomic Narratives from Social Media?

arXiv: https://arxiv.org/abs/2406.12109 · HTML: https://mlsanity.com/paper/2406.12109/

## Key facts

- Cited by 7 papers in the map (data through 14 Oct 2026).
- Builds on 14 of its 87 references that are in the map.
- First posted on arXiv 17 Jun 2024.

## Builds on (most cited first, 14 of 14)

- [BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding](https://mlsanity.com/paper/1810.04805/) (2018)
- [Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer](https://mlsanity.com/paper/1910.10683/) (2019)
- [RoBERTa: A Robustly Optimized BERT Pretraining Approach](https://mlsanity.com/paper/1907.11692/) (2019)
- [BloombergGPT: A Large Language Model for Finance](https://mlsanity.com/paper/2303.17564/) (2023)
- [A Dual-Stage Attention-Based Recurrent Neural Network for Time Series Prediction](https://mlsanity.com/paper/1704.02971/) (2017)
- [PIXIU: A Large Language Model, Instruction Data and Evaluation Benchmark for Finance](https://mlsanity.com/paper/2306.05443/) (2023)
- [Causal Inference in Natural Language Processing: Estimation, Prediction, Interpretation and Beyond](https://mlsanity.com/paper/2109.00725/) (2021)
- [Machine Learning Methods Economists Should Know About](https://mlsanity.com/paper/1903.10075/) (2019)
- [ChatGPT Informed Graph Neural Network for Stock Movement Prediction](https://mlsanity.com/paper/2306.03763/) (2023)
- [Language Models Trained on Media Diets Can Predict Public Opinion](https://mlsanity.com/paper/2303.16779/) (2023)
- [Twitter Speaks: A Case of National Disaster Situational Awareness](https://mlsanity.com/paper/1903.02706/) (2019)
- [Realised Volatility Forecasting: Machine Learning via Financial Word Embedding](https://mlsanity.com/paper/2108.00480/) (2021)
- [Efficacy of BERT embeddings on predicting disaster from Twitter data](https://mlsanity.com/paper/2108.10698/) (2021)
- [Multi-modal Attention Network for Stock Movements Prediction](https://mlsanity.com/paper/2112.13593/) (2021)

## Built on by (most cited first, 7 of 7)

- [Noise, Adaptation, and Strategy: Assessing LLM Fidelity in Decision-Making](https://mlsanity.com/paper/2508.15926/) (2025)
- [UCFE: A User-Centric Financial Expertise Benchmark for Large Language Models](https://mlsanity.com/paper/2410.14059/) (2024)
- [Energy Price Modelling: A Comparative Evaluation of four Generations of Forecasting Methods](https://mlsanity.com/paper/2411.03372/) (2024)
- [Causal Micro-Narratives](https://mlsanity.com/paper/2410.05252/) (2024)
- [Narrative Shift Detection: A Hybrid Approach of Dynamic Topic Models and Large Language Models](https://mlsanity.com/paper/2506.20269/) (2025)
- [Synthesizing Behaviorally-Grounded Reasoning Chains: A Data-Generation Framework for Personal Finance LLMs](https://mlsanity.com/paper/2509.14180/) (2025)
- [From Variance to Invariance: Qualitative Content Analysis for Narrative Graph Annotation](https://mlsanity.com/paper/2603.01930/) (2026)

## Abstract (arXiv)

This study empirically tests the textitNarrative Economics hypothesis, which posits that narratives (ideas that are spread virally and affect public beliefs) can influence economic fluctuations. We introduce two curated datasets containing posts from X (formerly Twitter) which capture economy-related narratives (Data will be shared upon paper acceptance). Employing Natural Language Processing (NLP) methods, we extract and summarize narratives from the tweets. We test their predictive power for textitmacroeconomic forecasting by incorporating the tweets' or the extracted narratives' representations in downstream financial prediction tasks. Our work highlights the challenges in improving macroeconomic models with narrative data, paving the way for the research community to realistically address this important challenge. From a scientific perspective, our investigation offers valuable insights and NLP tools for narrative extraction and summarization using Large Language Models (LLMs), contributing to future research on the role of narratives in economics.