Predicting Life Changes of Members of a Social Networking System

• US 20120016817A1
• Filed: 07/19/2010
• Published: 01/19/2012
• Est. Priority Date: 07/19/2010
• Status: Abandoned Application

• Current Assignee: Meta Platforms, Inc. (f/k/a Facebook, Inc.)
• Original Assignee: Meta Platforms, Inc. (f/k/a Facebook, Inc.)
• Inventors: Braginsky, David, Smith, S. Alex
• Application Number:
  US12/839,350
• Publication Number:
  US 20120016817A1
• Time in Patent Office: Days
• US Class Current: 706/12
• CPC Class Codes: G06N 20/00 Machine learning
• CPC Class Codes: G06N 5/02 Knowledge representation; Symbolic representation

Abstract

To predict a life change event for a user of the social networking system, such as a change in marital status, relationship status, employment status, etc., the disclosed system generates a training set of data comprising historical data of other users who have gone through a life change event. The system uses the training set data to generate a prediction algorithm using machine learning models. Furthermore, the system inputs the user data to the prediction algorithm to retrieve a prediction of whether the user will undergo one or more life change events. The system updates the user'"'"'s profile to indicate the life change event and provides advertisements to the user responsive to the prediction of one or more life change events.

Claims

1. A method for predicting a life change event of a user of a social networking system, the method comprising:

retrieving communication data associated with the user of the social networking system, the communication data comprising messages, wall posts, instant messages, feed posts or text messages;

parsing the communication data to obtain one or more key words indicative of a life change event;

predicting a life change event for the user responsive to the obtained key words; and

storing information about the prediction in association with the user data.

2. The method of claim 1, wherein life change event comprises a change in marital status, relationship status, age, employment status, graduation status, health status, addition of new children or death of a person associated with the user outside the social network.

3. The method of claim 1, wherein communication data received by the user within a particular time period is retrieved.

5. The method of claim 1, further comprising:

removing life change data from historical data responsive to a life change event occurring on a particular day.

6. The method of claim 1, further comprising:

selecting a content item for the user related to the detected life change event; and

sending the selected content to the user.

7. The method of claim 1, further comprising displaying one or more advertisements to the user selected based on the predicted life change event.

8. The method of claim 1, further comprising:

identifying users of the social networking system who have undergone a life change event;

determining life change event for each identified user; and

retrieving historical communications data associated with each identified user.

9. The method of claim 8, wherein users of social networking system who have undergone a life change event are identified based on user provided data.

4. The method of 1, wherein storing prediction information comprises updating the user profile associated with the social networking system.

10. A method for predicting a life change event of a user of a social networking system, the method comprising:

obtaining historical communications data that describes historical communications within the social networking system, the historical communications data associated with users who have undergone a life change event;

training a machine learning model using the obtained historical communications data;

obtaining information about communications associated with a particular use of the social networking system; and

predicting a life change event for the user using the machine learning model and the obtained information.

11. The method of claim 10, wherein life change event comprises a change in marital status, relationship status, age, employment status, graduation status, health status, addition of new children or death of a person or a pet associated with the user outside the social network.

12. The method of claim 10, wherein historical communications data comprises messages, wall posts, instant messages, photo comments, posted links, gifts, uploaded photos, videos and music associated with users of the social networking system who have undergone a life change event.

13. The method of claim 10, wherein historical communications data comprises communications associated with a user a week before the life change announcement by the user.

14. The method of claim 10, further comprising:

removing life change data from historical data responsive to a life change event occurring on a particular day.

15. The method of claim 10, further comprising:

selecting a content item for the user based on the predicted life change event; and

sending the selected content item to the user.

16. The method of claim 10, further comprising displaying one or more items to the user responsive to the predicted life change event.

17. The method of claim 10, further comprising:

identifying users of the social networking system who have undergone a life change event;

determining life change event for each identified user;

retrieving historical communications data associated with each identified user;

parsing the retrieved historical communications data to obtain a plurality of key words indicative of a life change event; and

obtaining the one or more key words within the communications data indicative of the life change event, each key word and associated life change event being used as signals to train the machine learning model.

18. The method of claim 17, wherein users of social networking system who have undergone a life change event are identified based on user provided data.