System and method for message reaction analysis

A system, comprising:

• a processor;
• a memory operatively connected to the processor and storing instructions that, when executed by the processor, cause:
• training a machine learning model, using a training data set of communication history data, to generate a trained machine learning model that maps standardized reaction data to one or more reactions proprietary to different communication services;
• obtaining current reaction data from a plurality of communications through the different communication services, wherein the current reaction data includes an audio data and a textual data;
• analyzing the current reaction data to generate current standardized reaction data that characterizes a sentiment of the reaction, wherein the analyzing includes vocal utterance analysis of the audio data and wherein the analyzing includes tone and sentiment analysis of the textual data;
• mapping, using the trained machine learning model, the current standardized reaction data to the one or more reactions proprietary to the different communication services to generate one or more identified reactions proprietary to the different communication services;
• storing the one or more identified reactions proprietary to the different communication services, that are mapped to the current reaction data;
• indexing the current reaction data based on the one or more identified reactions proprietary to the different communication services;
• and
• providing searching capability and message retrieval based on the indexing.

A non-transitory, computer-readable medium, storing instructions that, when executed by a processor, cause:

• training a machine learning model, using a training data set of communication history data, to generate a trained machine learning model that maps standardized reaction data to one or more reactions proprietary to different communication services;
• obtaining current reaction data from a plurality of communications through the different communication services;
• analyzing the current reaction data to generate current standardized reaction data that characterizes a sentiment of the reaction, and wherein the analyzing includes pausing patterns in the current reaction data, and wherein the analyzing further include resolving a conflict associated with the current reaction data from the plurality of communications through the different communication services;
• mapping, using the trained machine learning model, the current standardized reaction data to the one or more reactions proprietary to the different communication services to generate one or more identified proprietary reactions;
• and
• providing to the different communication services, the one or more identified reactions proprietary to the different communication services.