IP Library › Granted Patent US 12,293,289
Granted Patent B2
US 12,293,289 · App. 18/387,632 · Granted May 6, 2025

System to detect, assess and counter disinformation

Inventors: Elizabeth Charnock (Half Moon Bay, CA); Steve Roberts (Half Moon Bay, CA); Kathrin Haag (Edinburgh, GB)
Assignee: Chenope, Inc.
G06N3/08G06F16/951G06N3/04G06Q50/01G06F16/90332G06F40/186G06F40/205G06F40/279G06N5/025H04L63/302
View Patent ↗
Loading inventors, assignments & file history…
Monitor This Case
Get email alerts when status or documents change.
Order Certified Copies
Most orders are placed with the USPTO same day — all within 24 business hours.
Order via The Patent Place →
Pre-filled with this patent's details
Quick Facts
Patent No.
US 12,293,289
App. No.
18/387,632
Granted
May 6, 2025
Kind
B2
Abstract

A computer-readable medium for the identification, measurement, and combatting of the influence of large-scale creation and distribution of disinformation is herein disclosed. An embodiment of this invention is comprised of one or more repositories of data which involve online comments and articles and attributes derived from them, one or more technical targeting systems, a content analysis system, a cost and influence estimation system, a dialog system, a performance management system, a bot design and test system, a security system, a multimedia content generator, one or more machine learning components, a data collection mechanism, separate consumer and human operator applications, and a mechanism for the creation and management of bots across multiple channels.

Claims (28)

1. A technical targeting system for multi-evidence targeting, comprising:

graph processing server configured to accept messages from one or more message queues of online content, the one or more message queues fed by a data collection process encoding online content into data records for the one or more message queues,

one or more storage devices configured to store data and manage a knowledge base; and

one or more processors, configured to execute functionality for subsystems, components, and mechanisms stored in one or more non-transitory computer readable mediums, the one or more non-transitory computer readable mediums store subsystems, components, and mechanisms comprising:

a Natural Language Understanding/Natural Language Generation (NLU/NLG) subsystem configured to reference the knowledge base;

an assertion and event identification, extraction and analysis component configured to execute the NLU/NLG subsystem to extract the data from the accepted messages for storage into the one or more storage devices, the extracted data directed to assertions or references to real world events,

an influence measurement component configured to detect sentiment change from the stored data and label disinformation in the stored data based on the detection of coordination patterns,

a narrative and campaign identification component configured to identify one or more narratives from one or more sequences of disinformation from the stored data and one or more campaigns of disinformation regarding the real-world events within a bounded window of time.

2. The technical targeting system of claim 1 , wherein the one or more processors are configured to:

identify an at least one characteristic of disinformation based on one or more of:

presence of following processes, commands, and work schedules,

coordinated behavior,

sock puppet transfers,

anomalous echo chamber formulation,

content transmission patterns,

aspects of the online content being posted,

trajectories,

accounts being transitioned among multiple identities,

narrative transmission,

campaign participation,

inauthenticity in one or more of demographic, professional or domain

knowledge, employment status, physical location, and bot versus human,

characteristics displayed by bots,

behavior when confronted with system bots,

unstable lexical fingerprints,

malicious or adversarial actions,

unusual regularities in behavior, or

correlation to unusual changes in user behavior, Social Network Analysis (SNA), and image component reuse.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Nov 7, 2023
From: CHARNOCK, ELIZABETH; ROBERTS, STEVE; HAAG, KATHRIN
To: CHENOPE, INC.
Reel/Frame 065487/0509 →
Continuity (3)
Division 17003979 · Aug 26, 2020
Provisional Application 62891442 · Aug 26, 2019
Related Publication 20240070457A1 · Feb 29, 2024
References Cited (17)
US 8887286B2 · Dupont et al. · 2014 [cited by applicant]
US 10826937B2 · Irimie · 2020 [cited by examiner]
US 11200140B2 · Lin · 2021 [cited by examiner]
US 20170099200A1 · Ellenbogen · 2017 [cited by examiner]
US 20170345003A1 · Spears et al. · 2017 [cited by applicant]
US 20180102947A1 · Bhaya et al. · 2018 [cited by applicant]
US 20190005021A1 · Miller et al. · 2019 [cited by applicant]
US 20190208418A1 · Breu · 2019 [cited by applicant]
US 20190356684A1 · Sinha et al. · 2019 [cited by applicant]
US 20200104337A1 · Kelly · 2020 [cited by examiner]
Bracewell, D., Tomlinson, M. & Mohler, M. (2013). Determining the conceptual space of metaphoric expressions. In Computational Linguistics and Intelligent Text Processing (pp. 487-500), Springer. [cited by applicant]
Hansen, M. 1998. The function of Discourse Particles. A Study with Special Reference to Spoken Standard French. Pragmatics and Beyond New Series 53.) Amsterdam: John Benjamins. [cited by applicant]
http://rakhiv-mr.gov.ua/hutsulskyj-hovir/. [cited by applicant]
Lu, Xiaofei (2010). Automatic analysis of syntactic complexity in second language writing. International Journal of Corpus Linguistics, 15(4):474-496. [cited by applicant]
Michael Mohler, Bryan Rink, David Bracewell, and Marc Tomlinson. 2014. A Novel Distributional Approach to Multilingual Conceptual Metaphor Recognition. In Proceedings of COLING 2014, the 25th International Conference on… [cited by applicant]
Möller, Robert. “das Brötchen”, https://www.atlas-alltagssprache.de/brotchen/. [cited by applicant]
Stukal [et al.] (2019). The Use of Twitter Bots in Russian Political Communication. PONARS Eurasia Policy Memo No. 564. [cited by applicant]
Cited By (1)
US 12,730,970