1. A non-transitory computer readable medium comprising program code executable by a processor for causing the processor to: receive an electronic communication usable for training a neural network and comprising a plurality of characters; receive a sentiment dictionary comprising a plurality of expressions mapped to (i) a plurality of sentiment values representing different sentiments, (ii) a plurality of activation values representing different amounts of arousal, each expression of the plurality of expressions being mapped to a corresponding sentiment value of the plurality of sentiment values and a corresponding activation value of the plurality of activation values; determine a total sentiment score for the electronic communication by: segmenting the plurality of characters into a plurality of blocks of characters; determining, using the sentiment dictionary, a respective sentiment value for each block of characters in the plurality of blocks of characters; and aggregating the respective sentiment value for each block of characters in the plurality of blocks of characters; determine a total activation score for the electronic communication by: determining, using the sentiment dictionary, a respective activation value for each block of characters in the plurality of blocks of characters; and aggregating the respective activation value for each block of characters in the plurality of blocks of characters; determine an overall sentiment for the electronic communication by combining the total sentiment score and the total activation score; automatically construct training data usable for training the neural network based at least in part on the overall sentiment of the electronic communication, wherein the training data comprises a plurality of overall sentiments associated with a plurality of electronic communications usable for training the neural network; train the neural network using the training data; receive a second electronic communication comprising an unknown sentiment; and determine at least one sentiment associated with the second electronic communication using the neural network.