Sentiment analysis of content using expression recognition

A computerized-method for providing a sentiment score for a video meeting by evaluating expressions of participants during the video meeting, said computerized-method comprising:

• in a computerized system comprising a processor, a database of video meeting recordings;
• a memory to store the database, said processor is configured to operate a Sentiment Analysis (SA) module, said SA module is configured to:
• retrieving one or more recordings of a video meeting from the database of video meeting recordings of each participant in the video meeting and associating the one or more recordings with a participant;
• dividing each retrieved recording into segments;
• processing the segments in a Facial Expression Recognition (FER) system to associate each segment with a timestamped sequence of expressions for each participant in the video meeting;
• and
• processing each segment in an Artificial Neural Network (ANN) to yield a sentiment score for each statement for each participant,
• wherein a sentiment score of a statement for all participants in the video meeting is calculated by:
• adding the sentiment score of a statement for each participant to yield a total sentiment score for a statement;
• dividing the total sentiment score for a statement by a number of all the participants in the video meeting, to yield a score;
• and
• comparing the score with a predefined threshold to yield a final sentiment score for a statement for all participants, and
• wherein an overall sentiment score of a video meeting is calculated by:
• adding the final sentiment score for a statement for participants for each statement to yield a total sentiment score for all statements;
• dividing the total sentiment score for all statement by a number of all statements in the video meeting to yield a score;
• and
• comparing the score with a predefined threshold to yield an overall sentiment score for the video meeting.