Narrative Miners
Uncover the Stories That Drive Markets
Why?
Macro analysts know that the stories shaping economic and policy debates often come from the themes they are tracking, like “AI Bubble Concerns” or “Supply Chain Shifts.” These narratives appear across news, earnings calls, and regulatory filings, revealing how the conversation around key themes develops over time.
The NarrativeMiner class in the bigdata-research-tools package helps you systematically track the narratives you care about by:
- Defining custom narrative labels based on your themes of interest
- Monitoring how these narratives evolve across different document types
- Comparing public discourse with corporate messaging
- Identifying which companies or sectors are most linked to your targeted narratives
This notebook shows how to track the “AI Bubble Concerns” narrative, from label definition to document retrieval and narrative analysis, using LLMs.
Ready to get started? Let’s dive in!
Conclusion
The Narrative Miner stands as a powerful analytical framework that transforms unstructured textual data into actionable intelligence by identifying and tracking thematic narratives across diverse sources.
By layering document types, comparing what’s being said in news media against earnings transcripts and regulatory filings, users gain a multi-dimensional view of how narratives evolve and propagate. These patterns reveal not just what is being discussed, but how different stakeholders are positioning themselves relative to emerging trends.
The time-series visualization of narrative intensity often surfaces leading indicators of market sentiment shifts provides valuable foresight for investors seeking to anticipate market movements before they manifest in price action.
The NarrativeMiner’s flexibility allows it to be deployed across countless domains, from tracking sustainability commitments in corporate governance to identifying early signs of supply chain disruptions or monitoring the public reception of product innovations. Its integration with BigData’s search capabilities and modern LLM technology makes it particularly effective at processing large volumes of documents efficiently. As you incorporate narrative mining into your research workflow, consider experimenting with different narrative formulations, document sources, and time horizons to discover the combination that yields the most valuable signals for your specific analytical needs.
Enjoy exploring and extending your narrative analysis!
Narrative Miners
Uncover the Stories That Drive Markets
Why?
Macro analysts know that the stories shaping economic and policy debates often come from the themes they are tracking, like “AI Bubble Concerns” or “Supply Chain Shifts.” These narratives appear across news, earnings calls, and regulatory filings, revealing how the conversation around key themes develops over time.
The NarrativeMiner class in the bigdata-research-tools package helps you systematically track the narratives you care about by:
- Defining custom narrative labels based on your themes of interest
- Monitoring how these narratives evolve across different document types
- Comparing public discourse with corporate messaging
- Identifying which companies or sectors are most linked to your targeted narratives
This notebook shows how to track the “AI Bubble Concerns” narrative, from label definition to document retrieval and narrative analysis, using LLMs.
Ready to get started? Let’s dive in!
Conclusion
The Narrative Miner stands as a powerful analytical framework that transforms unstructured textual data into actionable intelligence by identifying and tracking thematic narratives across diverse sources.
By layering document types, comparing what’s being said in news media against earnings transcripts and regulatory filings, users gain a multi-dimensional view of how narratives evolve and propagate. These patterns reveal not just what is being discussed, but how different stakeholders are positioning themselves relative to emerging trends.
The time-series visualization of narrative intensity often surfaces leading indicators of market sentiment shifts provides valuable foresight for investors seeking to anticipate market movements before they manifest in price action.
The NarrativeMiner’s flexibility allows it to be deployed across countless domains, from tracking sustainability commitments in corporate governance to identifying early signs of supply chain disruptions or monitoring the public reception of product innovations. Its integration with BigData’s search capabilities and modern LLM technology makes it particularly effective at processing large volumes of documents efficiently. As you incorporate narrative mining into your research workflow, consider experimenting with different narrative formulations, document sources, and time horizons to discover the combination that yields the most valuable signals for your specific analytical needs.
Enjoy exploring and extending your narrative analysis!