US2017171346A1PendingUtilityA1

Evaluation of remote user attributes in a social networking environment

Assignee: SHUSTER GARY STEPHENPriority: Apr 17, 2008Filed: Nov 21, 2016Published: Jun 15, 2017
Est. expiryApr 17, 2028(~1.7 yrs left)· nominal 20-yr term from priority
H04L 9/0819G07F 17/32H04L 63/0209G07F 17/3276G06Q 30/02H04L 67/306H04W 4/029H04L 67/24H04L 67/104H04L 67/22H04W 4/02H04L 67/52
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Claims

Abstract

A computer host is configured to perform a method for defining user attributes with associated verification values for social networking accounts. The attributes concern the user's personal characteristics or attributes. The host publishes the attribute information to other clients together with interactive objects for soliciting corroboration of the attribute information. The host receives feedback information from other account holders, such as survey response data, concerning the veracity of the attribute information. The host processes the evaluation information and the feedback information to provide a veracity score of each attribute reported for each account holder, or for collections of attributes, by weighing the evaluation information and feedback information by a computed reliability factor for each source from which processed information is obtained.

Claims

exact text as granted — not AI-modified
What is claimed is: 
     
         1 . A method comprising:
 receiving an identity document comprising individual items of personal attribute information about a user of a communication service;   serving, by at least one computer, the personal attribute information about the user;   collecting, by the at least one computer, veracity feedback through the communication service comprising other users' opinions concerning veracity of the personal attribute information;   analyzing patterns in the veracity feedback to detect patterns that indicate the likelihood of collusion or fraud;   determining, by the at least one computer, a risk profile of the user that originated the personal attribute information in response to the veracity feedback;   adjusting the risk profile of the user based on a predetermined reliability score for each of the other users that provided the veracity feedback, wherein the predetermined reliability score is weighted at least in part on the likelihood of collusion or fraud; and   serving the risk profile by the at least one computer indicating a relative likelihood of truthfulness of the individual items of the personal attribute information.

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