Methods and systems for personalizing user experience based on personality traits

Patent metadata

Field	Value
Publication number	US-10148789-B2
Application number	US-201815948211-A
Country	US
Kind code	B2
Filing date	Apr 9, 2018
Priority date	Feb 24, 2017
Publication date	Dec 4, 2018
Grant date	Dec 4, 2018

Abstract

An electronic device associated with a media-providing service has one or more processors and memory storing instructions for execution by the one or more processors. The electronic device accesses a listening history of a user of the media-providing service. Based at least in part on the listening history of the user, the electronic device assigns a first personality trait of a plurality of personality traits to the user. The electronic device provides personalized content to the user based on the first personality trait.

First claim

What is claimed is:

1. A method, comprising
at an electronic device associated with a media-providing service having one or more processors and memory storing instructions for execution by the one or more processors:
assigning one or more characteristics of tracks to each personality trait of a plurality of personality traits, wherein the tracks are provided by the media-providing service;
accessing a listening history of a user of the media-providing service;
determining, based on the listening history of the user, that the user has consumed tracks having a first characteristic of the one or more characteristics, wherein the first characteristic is assigned to a first personality trait;
based at least in part on determining that the user has consumed the tracks having the first characteristic, assigning the first personality trait of the plurality of personality traits to the user;
determining, based on characteristics of tracks in the listening history of the user, a degree to which the user is associated with the first personality trait; and
providing personalized content to the user in accordance with a determination that the degree to which the user is associated with the first personality trait satisfies a threshold.

2. The method of claim 1 , wherein determining that the user has consumed the tracks having the first characteristic comprises determining that a number of tracks having the first characteristic in the listening history of the user satisfies a threshold.

3. The method of claim 1 , wherein determining the degree to which the user is associated with the first personality trait comprises determining a number of tracks having the first characteristic that have been consumed by the user.

4. The method of claim 1 , wherein assigning the one or more characteristics to at least one personality trait of the plurality of personality traits is performed based on a machine-learning algorithm.

5. The method of claim 1 , wherein the one or more characteristics include characteristics selected from the group consisting of moods and genres.

6. The method of claim 1 , further comprising, at the electronic device:
assigning one or more user behaviors to the first personality trait;
tracking behavior of the user; and
determining that a tracked behavior of the user corresponds to a first user behavior of the one or more user behaviors;
wherein assigning the first personality trait to the user is based at least in part on determining that the tracked behavior of the user corresponds to the first user behavior.

7. The method of claim 6 , wherein tracking behavior of the user comprises storing information about the tracked behavior in the listening history of the user.

8. The method of claim 6 , wherein tracking the user behavior includes tracking use of a shuffle feature by the user.

9. The method of claim 6 , wherein tracking the user behavior includes tracking use of a skip feature by the user.

10. The method of claim 9 , wherein:
tracking the use of the skip feature comprises counting a number of tracks the user skips before completing playback; and
assigning the first personality trait to the user comprises labeling the user as neurotic in response to determining that the number of tracks the user skips satisfies a threshold.

11. The method of claim 1 , further comprising, at the electronic device:
assigning the user a second personality trait based at least in part on the listening history of the user; and
providing personalized content to the user based on the second personality trait.

12. The method of claim 1 , wherein providing the personalized content comprises changing a tone of voice for messages for presentation to the user based on the first personality trait.

13. The method of claim 1 , wherein providing the personalized content comprises promoting, to the user, a content source associated with the first personality trait.

14. The method of claim 1 , wherein providing the personalized content comprises selecting tracks to recommend to the user from one or more content sources of the media-providing service.

15. The method of claim 14 , wherein the one or more content sources of the media-providing service comprise one or more radio stations.

16. The method of claim 1 , further comprising, at the electronic device, determining an interest level corresponding to a user preference for a first content type over a second content type, based at least in part on the assigned personality trait;
wherein the personalized content is provided to the user based on the interest level.

17. The method of claim 16 , wherein the interest level is an interest level in a message.

18. The method of claim 1 , wherein assigning the first personality trait to the user is further based at least in part on one or more demographic variables for the user.

19. The method of claim 1 , wherein the plurality of personality traits is selected from the group consisting of openness, agreeableness, extroversion, neuroticism, and conscientiousness.

20. The method of claim 1 , wherein the plurality of personality traits corresponds to the Meyers-Briggs personality model.

21. An electronic device of a media-providing service, comprising:
one or more processors; and
memory storing one or more programs for execution by the one or more processors, the one or more programs comprising instructions for:
assigning one or more characteristics of tracks to each personality trait of a plurality of personality traits, wherein the tracks are provided by the media-providing service;
accessing a listening history of a user of the media-providing service;
determining, based on the listening history of the user, that the user has consumed tracks having a first characteristic of the one or more characteristics, wherein the first characteristic is assigned to a first personality trait;
based at least in part on determining that the user has consumed the tracks having the first characteristic, assigning the first personality trait of the plurality of personality traits to the user;
determining, based on characteristics of tracks in the listening history of the user, a degree to which the user is associated with the first personality trait; and
providing personalized content to the user in accordance with a determination that the degree to which the user is associated with the first personality trait satisfies a threshold.

22. A non-transitory computer-readable storage medium storing one or more programs configured for execution by an electronic device of a media-providing service, the one or more programs comprising instructions for:
assigning one or more characteristics of tracks to each personality trait of a plurality of personality traits, wherein the tracks are provided by the media-providing service;
accessing a listening history of a user of the media-providing service;
determining, based on the listening history of the user, that the user has consumed tracks having a first characteristic of the one or more characteristics, wherein the first characteristic is assigned to a first personality trait;
based at least in part on determining that the user has consumed the tracks having the first characteristic, assigning the first personality trait of the plurality of personality traits to the user;
determining, based on characteristics of tracks in the listening history of the user, a degree to which the user is associated with the first personality trait; and
providing personalized c

Assignees

• Spotify Ab

Inventors

• Gibson Clay
• Shapiro Will
• Gil Santiago
• Anderson Ian
• Mpossi Margreth
• Semerci Oguz
• Wolf Scott

Classifications

• H04L67/22

  Electricity · mapped topic

• H04L67/327 Primary

  Electricity · mapped topic

• H04L67/306 Primary

  User profiles · CPC title

• H04L67/142

  Managing session states for stateless protocols; Signalling session states; State transitions; Keeping-state mechanisms · CPC title

• H04L67/63 Primary

  Routing a service request depending on the request content or context · CPC title