System and Method to Optimize Content Order to Maintain Sentiment Within a Set of Thresholds
Publication Date: 2013-Apr-16
The IP.com Prior Art Database
Disclosed is a system to intelligently order content for consumption in a manner that maintains a sentiment or mood threshold range.
Page 01 of 3
System and Method to Optimize Content Order to Maintain Sentiment Within a Set of
An individual's mood can be altered by reading news article, viewing social media posts, or listening to music. Currently in the art, there are many patents around using mood as triggers, such as building play lists based on a mood; filtering content based on mood, making suggestions based on a mood, etc. However, the current art is deficient in that content is being narrowed or filtered based on the user's existing mood and may cause the user to miss important content, particularly in news, social media, etc.
A method is needed to define a desired range for a user's mood in which to stay, and then reorder content such that the user views or absorbs all content but maintain a mood threshold or range.
The invention is a novel and non-obvious system to intelligently order content for consumption in a manner that maintains a sentiment or mood threshold range.
To implement the invention in a preferred embodiment:
1. User defines a desired mood threshold to stay within a parameter based on
A. A numerical scale, such as 1-10 where 10 is maximum "happiness" level or whatever the user defines the "mood"
B. Day/time; user may be more open to a range of mood on certain days
2. User defines a target mood level for a certain time. A user may have a desire to consume media in an order that assists in achieving a mood level by a certain time or an event on a calendar (e.g., start consuming social media or other content at 2PM in order to set a mood level for a 5PM dinner date)
3. Over time, measure the level impact different content has on the user's mood. A user's mood response to various types of content may be measured over time using existing art. The reaction might consist of mood alterations based on topics/events, songs/genre, people/users in social media (based on previous interactions, sentiment analysis of post or message, historical responses, personality type...