Passive sharing

• US 9,984,378 B2
• Filed: 10/19/2011
• Issued: 05/29/2018
• Est. Priority Date: 10/19/2011
• Status: Active Grant

• Current Assignee: Meta Platforms, Inc. (f/k/a Facebook, Inc.)
• Original Assignee: Meta Platforms, Inc. (f/k/a Facebook, Inc.)
• Inventors: Liu, Deborah
• Primary Examiner(s): Pond, Robert M
• Application Number:
  US13/276,968
• Publication Number:
  US 20130103534A1
• Time in Patent Office: 2,414 Days
• Field of Search: 705 267, 705 26, 705 27
• CPC Class Codes: G06Q 30/0201 Market modelling; Market analysis; Collecting market data
• CPC Class Codes: G06Q 30/0282 Rating or review of business operators or products
• CPC Class Codes: G06Q 30/0631 Item recommendations
• CPC Class Codes: G06Q 50/01 Social networking

Abstract

A social networking system leverages information obtained regarding user interactions with applications hosted through the social networking system as well as information obtained regarding purchases of application-related digital items and digital currencies to provide insight into user behavior. The social networking system can use these insights to enhance the user'"'"'s experience of the applications, purchases, and the social networking system generally. For example, the social networking system can customize transaction flows, provide credit referrals, and provide users with aggregated yet personally tailored sales information.

Claims

1. A method comprising:

storing in a social networking system a plurality of user profiles for a plurality of users, the user profiles comprising connection information indicating connections between the users of the social networking system as well as histories of application use by users of applications hosted by third party systems and presented on a same interface as the social networking system;

receiving transaction information for the users, the transaction information identifying items purchased and the users who purchased the items, the items being able to be used within the applications;

aggregating, by a computer processor of the social networking system, the transaction information for items purchased by a subset of the users sharing a direct connection with a user of the social networking system;

determining, by the computer processor, an item of interest to the user to be used in conjunction with an application of the applications based on the aggregated transaction information and based on whether the user'"'"'s purchase history indicates that the user has previously purchased items to be used in conjunction with the application;

sending the aggregated transaction information regarding the item of interest to the user; and

responsive to the user purchasing items to be used in conjunction with an application;

determining one or more users of the subset of users to be provided with bonus credits; and

sending a list of the one or more users of the subset of users describing potential recipients of bonus credits based on the aggregated transaction information, wherein the one or more users are determined based on a predicted likelihood by a machine learned algorithm that the one or more users will purchase additional credits if awarded bonus credits.

2. The method of claim 1 wherein determining the item of interest to the user comprises determining that the item of interest has aggregated sales higher than other items.

3. The method of claim 1 wherein determining the item of interest to the user comprises determining, based on the aggregated transaction information, that a new seller is selling the item of interest.

4. The method of claim 1 wherein determining the item of interest to the user comprises determining that a current price of the item of interest has decreased relative to a past price.

5. The method of claim 1 wherein determining the item of interest to the user comprises determining whether the item of interest is relevant to the user based on the user'"'"'s history of digital currency purchases.

6. The method of claim 1 wherein the information sent to the user regarding the item of interest to the user comprises an aggregate price of the item from other sellers of the item of interest.

7. The method of claim 6 wherein the aggregate price is at least one of a median price, an average price, a historical price, and a mode price.

8. A computer comprising:

a processor for executing computer program modules; and

a non-transitory computer-readable storage medium storing executable computer program modules comprising;

a user profile store configured to store in a social networking system a plurality of user profiles for a plurality of users, the user profiles comprising connection information indicating connections between the users of the social networking system as well as histories of application use by users of applications hosted by third party systems and presented on a same interface as the social networking system;

a web server configured to receive transaction information for the users, the transaction information identifying items purchased and the users who purchased the items, the items being able to be used within the applications; and

a credit engine configured to;

aggregate the transaction information for items purchased by a subset of the users sharing a direct connection with a user of the social networking system;

determine an item of interest to the user to be used in conjunction with an application of the applications based on the aggregated transaction information and based on whether the user'"'"'s purchase history indicates that the user has previously purchased items to be used in conjunction with the application;

send the aggregated transaction information regarding the digital item of interest to the user; and

responsive to the user purchasing items to be used in conjunction with an application;

determine one or more users of the subset of users to be provided with bonus credits; and

send a list of the one or more users of the subset of users describing potential recipients of bonus credits based on the aggregated transaction information, wherein the one or more users are determined based on a predicted likelihood by a machine learned algorithm that the one or more users will purchase additional credits if awarded bonus credits.

9. The computer of claim 8 wherein determining the item of interest to the user comprises determining that the item of interest has aggregated sales higher than other digital items.

10. The computer of claim 8 wherein determining the item of interest to the user comprises determining, based on the aggregated transaction information, that a new seller is selling the item of interest.

11. The computer of claim 8 wherein determining the item of interest to the user comprises determining that a current price of the item of interest has decreased relative to a past price.

12. The computer of claim 8 wherein determining the item of interest to the user comprises determining whether the item of interest is relevant to the user based on the user'"'"'s history of digital currency purchases.