Narrative intelligence

"Narrative intelligence" also has older meanings in other fields. In cognitive science and artificial-intelligence research it refers to the ability of people or systems to understand and produce stories. This entry uses the term in the sense common in media and risk analysis: intelligence about narratives circulating in public information. If you searched for the research meaning, the concepts are related only by the word "narrative".

Where media monitoring asks what has been published about a subject, narrative analysis asks what story is being told and how it is moving. An analyst first identifies a narrative, a recurring claim or framing, such as "the company is hiding a defect". The analyst then traces it: the earliest appearance, the accounts and outlets that carry it, changes in wording, the communities it moves between, and the point at which mainstream outlets pick it up.

Technique combines several methods. Text clustering groups posts and articles that make the same claim in different words. Network analysis shows which accounts amplify one another. Timeline analysis marks spikes and their upstream causes. Provenance research uses OSINT methods to check whether the accounts pushing a narrative are what they claim to be, which links the work to coordinated inauthentic behavior and information operations analysis.

A narrative might be a false claim about a product ingredient that starts in a small forum, jumps to a widely followed account, and later appears in a regional news story that quotes "social media reports". Or it might be a framing of a merger as a job-loss story that different stakeholders adopt independently. The analytical output is a map of the narrative and a judgment about whether it is organic, organized or a mix.

A volume chart shows that something is happening. Narrative analysis shows what the something is, which is what a spokesperson needs. It supports decisions on whether to respond, to whom, with what message, and whether the issue should be escalated to security or legal teams.

The data pool is widening beyond news and social. Language models now summarize narratives about companies for their users, which makes the sources those models retrieve part of the analysis. See AI visibility.

Narrative intelligence is not the same as sentiment analysis. Sentiment labels tone; narrative analysis identifies content and movement. It is also not attribution. Showing how a narrative spread does not prove who started it, and careful analysts state the difference. And it is not automatic: software clusters and surfaces, but judging whether a cluster is meaningful is analyst work.

Scope matters too. A narrative analysis covers the sources that were collected, so a report should state which outlets, platforms and date ranges it includes. A conclusion that a claim "originated" in a given forum means it was earliest among the material collected, not necessarily earliest anywhere.