# US 11,444,991 B2 · Social sharing system

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- Number: US 11,444,991 B2
- Document ID: US11444991B2
- Status: Granted
- Kind: B2
- Application number: 16/983,846
- Filed: 2020-08-03
- Published: 2021-03-25
- Granted: 2022-09-13
- Earliest claimed: 2012-08-07
- Assignees: Paypal, Inc.
- Applicants: PayPal, Inc.
- Inventors: Neelakantan Sundaresan; Atish Das Sarma; Si Si; Elizabeth Churchill
- Web page: https://patentgrep.com/patent/US11444991B2

## CPC

- G06Q 10/48: using social graphs
- G06Q 10/42: Determination of affinities or common interests between users
- H04L 65/403: Arrangements for multi-party communication, e.g. for conferences (data switching systems for conference H04L12/18; arrangements for connecting several subscribers to a common circuit, i.e. affording conference facilities H04M3/56; television conferencing systems H04N7/15)
- G06Q 30/0255: {based on user history}
- G06Q 30/0271: {Personalized advertisement}
- G06Q: INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- H04L: TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION (arrangements common to telegraphic and telephonic communication H04M)

## Abstract

A system, computer-readable storage medium storing at least one program, and computer-implemented method for providing recommendations based on social network sharing activity. Sharing activity relating to the sharing of the content item on a social network by a first user is accessed. Consumption information related to the consumption of the content item. A correlation between the sharing activity and the consumption information is determined. A recommendation is then generated based on the correlation.

## Claims

### Claim 1

A system comprising:
one or more processors; and
one or more machine-readable storage media having instructions stored thereon that, in response to being executed by the one or more processors, cause the system to perform operations comprising:
obtaining user data for a first and second user from a social network, the user data for the first and second users including consumption information that relates to content items shared between the first and second users;
determining a set of relationship attributes of the first and second users, wherein one of the set of relationship attributes defines a relationship between the first user and the second user;
subsequent to the determining, identifying a third user based on the relationship attribute of the first and second users, wherein user data of the third user includes the relationship attribute, indicating that the third user has the same relationship with the first user that exists between the first user and the second user;
determining recommendation content items for the third user based on the consumption information; and
presenting the recommendation content items to the third user via a user interface on a device associated with the third user.

### Claim 2 (depends on 1)

The system of claim 1, wherein the user data further includes social network connection information that relates to connections between users of the social network.

### Claim 3 (depends on 1)

The system of claim 1, wherein determining the recommendation content items for the third user includes determining a correlation between consumption of a content item and the relationship attributes.

### Claim 4 (depends on 1)

The system of claim 1, wherein the operations further comprise:
in response to the identifying of the third user, determining a correlation of content items, wherein the correlation of content items includes a comparing with content items consumed.

### Claim 5 (depends on 4)

The system of claim 4, wherein the recommendation content items are determined based in part on the determining of the correlation of content items.

### Claim 6 (depends on 5)

The system of claim 5, wherein the correlation of the content items can include the price, category, and type of items.

### Claim 7 (depends on 1)

The system of claim 1, wherein determining the recommendation content items for the third user includes determining a correlation between a platform used to share a content item and consumption of the content item.

### Claim 8

A method comprising:
obtaining user data for a first and second user from a social network, the user data for the first and second users including consumption information that relates to content items shared between the first and second users;
determining a set of relationship attributes of the first and second users, wherein one of the set of relationship attributes defines a relationship between the first user and the second user;
subsequent to the determining, identifying a third user based on the relationship attribute of the first and second users, wherein user data of the third user includes the relationship attribute, indicating that the third user has the same relationship with the first user that exists between the first user and the second user;
determining recommendation content items for the third user based on the consumption information; and
presenting the recommendation content items to the third user via a user interface on a device associated with the third user.

### Claim 9 (depends on 8)

The method of claim 8, wherein the user data further includes social network connection information that relates to connections between users of the social network.

### Claim 10 (depends on 8)

The method of claim 8, wherein determining the recommendation content items for the third user includes determining a correlation between consumption of a content item and the relationship attribute.

### Claim 11 (depends on 8)

The method of claim 8, further comprising:
in response to the identifying of the third user, determining a correlation of content items, wherein the correlation of content items includes a comparing with content items consumed.

### Claim 12 (depends on 11)

The method of claim 11, wherein the recommendation content items are determined based in part on the determining of the correlation of content items.

### Claim 13 (depends on 8)

The method of claim 8, wherein determining the recommendation content items for the third user includes determining a negative correlation between sharing a content item and consumption of the content item.

### Claim 14

A non-transitory machine-readable medium having stored thereon machine-readable instructions executable to cause a machine to perform operations comprising:
obtaining user data for a first and second user from a social network, the user data for the first and second users including consumption information that relates to content items shared between the first and second users;
determining a set of relationship attributes of the first and second users, wherein one of the set of relationship attributes defines a relationship between the first user and the second user;
subsequent to the determining, identifying a third user based on the relationship attribute of the first and second users, wherein user data of the third user includes the relationship attribute, indicating that the third user has the same relationship with the first user that exists between the first user and the second user;
determining recommendation content items for the third user based on the consumption information; and
presenting the recommendation content items to the third user via a user interface on a device associated with the third user.

### Claim 15 (depends on 14)

The non-transitory machine-readable medium of claim 14, wherein the user data further includes social network connection information that relates to connections between users of the social network.

### Claim 16 (depends on 14)

The non-transitory machine-readable medium of claim 14, wherein determining the recommendation content items for the third user includes determining a correlation between consumption of a content item and the relationship attribute.

### Claim 17 (depends on 14)

The non-transitory machine-readable medium of claim 14, wherein the operations further comprise:
applying a set of filters to the user data to omit a portion of the user data collected before a particular time.