Causal Modeling and Attribution
First Claim
1. A method, comprising:
- receiving input data as a representation of communications between two or more users;
determining causal relationships between the two or more users based in part on the input data that represents the communications;
determining one or more influence variables that influence the causal relationships between the two or more users; and
generating a causal relationships model based on the one or more influence variables and the causal relationships between the two or more users, the causal relationships model representative of causality, influence, and attribution between the two or more users.
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Abstract
In techniques for causal modeling and attribution, a causal modeling application implements a dynamical causal modeling framework. Input data is received as a representation of communications between users, such as social media interactions between social media users, and causal relationships between the users can be determined based in part on the input data that represents the communications. Influence variables, such as exogenous variables and/or endogenous variables, can also be determined that influence the causal relationships between the users. A causal relationships model is generated based on the influence variables and the causal relationships between the users, where the causal relationships model is representative of causality, influence, and attribution between the users.
26 Citations
20 Claims
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1. A method, comprising:
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receiving input data as a representation of communications between two or more users; determining causal relationships between the two or more users based in part on the input data that represents the communications; determining one or more influence variables that influence the causal relationships between the two or more users; and generating a causal relationships model based on the one or more influence variables and the causal relationships between the two or more users, the causal relationships model representative of causality, influence, and attribution between the two or more users. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10)
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11. A computing device, comprising:
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a memory configured to maintain input data that is received as a representation of social media interactions between two or more users; a processor system to implement a causal modeling application that applies a dynamical causal modeling framework that is configured to; determine causal relationships between the two or more users based in part on the input data that represents the social media interactions; determine one or more influence variables that influence the causal relationships between the two or more users; and generate a causal relationships model based on the one or more influence variables and the causal relationships between the two or more users. - View Dependent Claims (12, 13, 14, 15, 16, 17)
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18. A computer-readable storage memory comprising a causal modeling application stored as instructions that are executable and, responsive to execution of the instructions by a computing device, the computing device performs operations of the causal modeling application comprising to:
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receive input data as a representation of communications between two or more users; determine causal relationships between the two or more users based in part on the input data that represents the communications; determine one or more influence variables that influence the causal relationships between the two or more users; and generate a causal relationships model based on the one or more influence variables and the causal relationships between the two or more users. - View Dependent Claims (19, 20)
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Specification