Bibliographic Details
| Title: |
Crypto Whitepaper Syntactic Sovereignty: Persuasive Grammar as Financial Authority |
| Authors: |
Startari, Agustin V. |
| Publisher Information: |
AI. Power and Discourse, 2025. |
| Publication Year: |
2025 |
| Subject Terms: |
Machine Learning/ethics, Linguistics/statistics & numerical data, Artificial intelligence, Cryptocurrencies, Artificial Intelligence/legislation & jurisprudence, Artificial Intelligence/statistics & numerical data, Comparative linguistics--Statistical methods, Linguistics/legislation & jurisprudence, Artificial Intelligence/standards, crypto, Business models, Unsupervised Machine Learning/classification, Machine Learning, Linguistics/history, Cohesion (Linguistics), Cryptocurrencies--Law and legislation, Supervised Machine Learning/economics, Heuristics/ethics, Indifferentism (Ethics) in literature, Business, Machine Learning/standards, Big business--Mathematical models, Linguistics/trends, Banks and banking--Insurance business, Linguistics/standards, Artificial Intelligence/ethics, Supervised Machine Learning/ethics, Machine Learning/supply & distribution, Linguistics/methods, Linguistics/classification, Linguistics/organization & administration, Linguistics/education, Supervised Machine Learning/classification, Better business bureaus, Machine Learning/trends, Unsupervised Machine Learning/ethics, Classifiers (Linguistics), Ethics Consultation/ethics, Machine Learning/history, Artificial Intelligence/classification, Community finance, Business policy, Accounting--Professional ethics, Supervised Machine Learning, Justification (Ethics), Abattoirs/ethics, Ethics Committees, Research/ethics, Classification--Books--Linguistics, Artificial Intelligence/economics, Causative (Linguistics), Supervised Machine Learning/trends, Unsupervised Machine Learning/history, Business economics, Linguistics/ethics, Business intelligence, Artificial Intelligence/history, Applied linguistics--Research, Artificial Intelligence, Supervised Machine Learning/standards, Monetary and finances, Machine Learning/classification, Machine learning, Machine learning--Experiments, Comparative linguistics, Artificial Intelligence/trends, Ethics, Business, Machine Learning/legislation & jurisprudence, Categorization (Linguistics), Ethics, Big business--Social aspects, Ethics Committees, Clinical/ethics, Linguistics/economics, Linguistics, Classifiers (Linguistics)--Data processing, Machine learning--Technique, Public finance, Administrative agencies--Finance--Auditing, Artificial Intelligence/supply & distribution, Machine Learning/economics, Academic libraries--Finance, Ensemble learning (Machine learning), Finances, Accountants--Professional ethics, Cartesian linguistics, Machine learning--Evaluation, FOS: Languages and literature, Banks and banking--Insurance business--State supervision, Accounting/ethics, Linguistics/instrumentation, Big business--Corrupt practices, Unsupervised Machine Learning |
| Description: |
This article investigates how persuasive syntactic structures embedded in AI-generated crypto whitepapers function as a vehicle of financial authority. Drawing from a curated corpus of 10,000 whitepapers linked to token launches between January 2022 and March 2025, we apply transformer-based dependency parsing to extract high-weighted grammatical features, including nested conditionals, modality clusters, and assertive clause chaining. We operate these patterns via a Deceptive Syntax Anomaly Detector (DSAD), which computes a syntactic risk index and identifies recurrent grammar configurations statistically correlated with anomalous capital inflows and subsequent collapses (Spearman correlation, ρ > 0.4, p 0.4, p |
| Document Type: |
Article |
| Language: |
English |
| DOI: |
10.17613/xwx1x-vpy25 |
| DOI: |
10.5281/zenodo.16044858 |
| DOI: |
10.17613/7qc4p-76g04 |
| DOI: |
10.5281/zenodo.16044857 |
| Rights: |
CC BY |
| Accession Number: |
edsair.doi.dedup.....9a3b8e3a775afcd7c38550efdec8f7d8 |
| Database: |
OpenAIRE |
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