Semiotics and Influence Research

1. What observable features of a message — sign, frame, format, timing — predict its propagation across platforms, independent of its author?
2. Which signals distinguish coordinated influence activity from organic spread in public data, and at what precision?
3. How do the semiotic conventions of a genre — a press release, a release announcement, a campaign — shape what audiences take from it?

• Corpus studies of public, published material only, with the collection criteria written before collection starts.
• Coding by a documented codebook with inter-rater reliability reported, not by a single reader's judgement.
• Detection work evaluated against labelled public datasets, with precision and recall stated for every claim.
• Analysis code and derived datasets published; raw material cited to its public source rather than redistributed.

• The programme studies influence; it does not conduct it. No campaign, test message or audience experiment is run on anybody.
• No private data, no scraping behind a login, no data on identifiable individuals beyond what a cited public source already states.
• No work is undertaken for a client that would apply the findings to persuade a population; the output is papers, methods and detection tools.

• 2026 Q4in progressCodebook and corpus criteria for the first semiotics study, published
• 2025 Q3doneFirst semiotics paper on SSRN
• 2027 Q2plannedFirst corpus-study preprint

Full roadmap

• Ticketstorm as Mass Visual Disruption — SSRN, 2025-09-07

Federal programmes whose published scope this work falls within. None has been applied to; see the grants page for what has to exist first.

• NSF — Social, Behavioral and Economic Sciences (SBE). Communication, language and cognition research on how messages are interpreted and spread.
• NSF — Secure and Trustworthy Cyberspace (SaTC). Detection of coordinated inauthentic behaviour in online systems is within scope.