System and method for analyzing and predicting emotion reaction

Abstract

The present invention provides a method for identifying trends and correlation of content items characteristics in relation to user emotional reaction. The method comprising the steps of: receiving plurality of rating/votes originated by different users relating one or more content item, wherein the user is required to selection emotion icon from multiple choice emotion icons, analyzing statistics of users selections by identifying characteristics of the news/article item, including at least one of; timing of news item publication, subject of content item, source/writer of the content, context of the content, style of content, key words/image appearing in the content and identifying correlations of content item characteristics in relation user emotion reaction according to the said analysis identifying trends.

What is claimed is: 
     
         1 . A method for managing content items location within communication network, said method comprising the steps of:
 receiving plurality of emotion reactions, rating or votes originated by different users relating one or more content item through time;   analyzing statistics of users reactions in relation to characteristics of the content item, including at least one of; timing of content item publication, subject of content item, source/writer of the content, context of the content, style of content, key words/image appearing in the content; and   clustering content item by identifying correlations of content item characteristics in relation user emotion reaction according to the said emotion statistics analysis;   managing content page layout publication by estimating optimal location for at least one content item within content page based on the emotional reactions;   wherein at least one of receiving, analyzing, clustering or managing is performed by at least one processor.   
     
     
         2 . The method of  claim 1  further comprising the steps of:
 predicting engagement and ads clicking rating of content items based content items clustering and correlation of content items characteristics in relation to user emotional reaction, wherein the content items management is based on said predictions. 
 
     
     
         3 . The method of  claim 1  further comprising the steps of:
 Estimating optimal content item publication time periods based on emotion responses analysis in relation to content item characteristics, wherein the content items management is based on said estimation. 
 
     
     
         4 . A method for publish timing and selecting content items or advertisements in a web page, said method comprising the steps of:
 receiving plurality of emotional rating/votes originated by different users relating one or more content item, wherein the user is required to selection emotion icon from multiple choice emotion icons;   analyzing statistics of users selections by identifying characteristics of the content item, including at least one of; timing of news item publication, subject of content item, source/writer of the content, context of the content, style of content, key words/image appearing in the content; and   recommending of content items and timing of publication according to the said analysis.   
     
     
         5 . The method of  claim 1  further comprising the steps of:
 Context text analysis of content items, identify trending topics, analyzing behavior patterns of different users in relation to common content items and content item clustering based on the context text analysis and behavior pattern analysis, wherein said context analyzing data is added to content item characteristics. 
 
     
     
         6 . The method of  claim 1  further comprising the step of predicting time period exposer of content of content item based on measured emotion in relation to content item characteristics reaction, wherein exposure period provide estimation to the content provider how much time to keep the content exposed to the user or promoting said content item;
 wherein the content items management is based on said predictions. 
 
     
     
         7 . The method of  claim 1  further comprising the step of predicting user emotion reaction, where the user's didn't provide such reaction based on analyzed emotion reactions to sequence of reading content items of other users, which expressed their emotion. 
     
     
         8 . The method f  claim 1  further comprising the step of adapt advertising type based on prediction of the emotional state or mood which predict adverting success rate based on measured user emotions. 
     
     
         9 . The method of  claim 1  wherein the estimation of page location of the content item is further based on analyzing content item characteristics. 
     
     
         10 . A system for managing content item publication in communication network, said system comprised of:
 Emotion measurement module for receiving plurality of emotion reactions originated by different users relating one or more content item;   Emotion analyzing module analyzing statistics of users reactions in relation to characteristics of the content item, including at least one of; timing of news item publication, subject of content item, source/writer of the content, context of the content, style of content, key words/image appearing in the content and clustering content item by identifying correlations of content item characteristics in relation user emotion reaction   Content wizard module for estimating optimal content page location based on the emotional reactions and predict best page content location by analyzing content in relation to content item characteristics.   
     
     
         11 . The system of  claim 9  further comprising prediction module for predicting engagement and ads clicking rating of content items based on correlation of content items characteristics in relation to user emotional reaction, wherein the content items management is based on said predictions. 
     
     
         12 . The system of  claim 9  further comprising prediction module for estimating optimal content item publication time periods based on emotion responses analysis in correlation of content items characteristics, wherein the content items management is based on said predictions. 
     
     
         13 . The system of  claim 9  wherein the context analyzing module further comprises context text analysis of content items, identify trending topics, analyzing behavior patterns of different users in relation to common content items or article clusters and article clustering based on the context text analysis and behavior pattern analysis, wherein the content items management is based on said predictions. 
     
     
         14 . The system of  claim 9  further comprising prediction module for predicting time period exposer of content of content item based on measured emotion in relation to content item characteristics reaction, wherein exposure period provides estimation to the content provider how much time to keep the content exposed to the user or promoting said content item, wherein the content items management is based on said predictions. 
     
     
         15 . The system of  claim 9  further comprising prediction module predicting user emotion reaction, where the user's didn't provide such reaction based on analyzed emotion reactions to sequence of reading content items of other users, which expressed their emotion, wherein the content items management is based on said predictions. 
     
     
         16 . The system of  claim 1  further comprising prediction module for determining advertising type or/and advertising optimal publication time based on prediction of the emotional state or mood which predict adverting success rate based on measured user emotions.