Abstract: Disclosed is an image analysis system which includes a first analyzer and a second analyzer. The first analyzer generates first features by encoding images through a first model and adjusts a weight of the first model based on the first features. The second analyzer generates second features based on the first features by encoding the images through a second model, classifies the second features into classes, respectively, and adjusts a weight of the second model based on mutual information and a correlation between a first class among the classes which features corresponding to an original image group from among the second features are classified as and a second class among the classes which features corresponding to an augmentation group of the original image group from among the second features are classified as.

Abstract: Systems, methods, and non-transitory computer readable media can obtain a conversation of a user in a chat application associated with a system, where the conversation includes one or more utterances by the user. An analysis of the one or more utterances by the user can be performed. A sentiment associated with the conversation can be determined based on a machine learning model, wherein the machine learning model is trained based on a plurality of features including demographic information associated with users.