Use of Machine-Learning Models in Creating Messages for Advocacy Campaigns
AssigneeFiscalNote, Inc.
InventorsVladimir Eidelman, Daniel Argyle, Paul Matthew Ellender, JR., Anastassia Kornilova
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AssigneeFiscalNote, Inc.
InventorsVladimir Eidelman, Daniel Argyle, Paul Matthew Ellender, JR., Anastassia Kornilova
Estimating the term…
An advocacy system uses trained machine learning models to create messages that are sent to advocates or policymakers to achieve desired outcomes for an organization. Desired outcomes can include, for example: an advocate sending a message to a policymaker or legislative representative advocating in favor or the organization's position on an issue; a policymaker acting or voting in favor of the organization's position on an issue; or an advocate making a financial contribution to the organization. The machine learning models can be configured to select possible message characteristics or features that the system will include/use in creating/sending messages to/for individual senders and recipients. The machine learning models can be trained based on message characteristics, personal profile characteristics of senders/recipients, and outcomes from previously sent messages. Personal profile characteristics of senders/recipients can indicate correlations between certain message characteristics and certain outcomes of sending messages.
A method performed by a computer system having at least one processor and a memory, the method comprising, the computer system:
Dependencies are inferred from the claim text.