An emotion determining method for multiple rounds of questions and answers, relating to the field of semantic recognition in artificial intelligence. The method comprises: segmenting a question-and-answer text into several groups of question text segments and several answer text segments; inputting all the question text segments and the answer text segments to a trained model, and respectively encoding each group of the question text segments and answer text segments into matrices, wherein words in the question text segments and the answer text segments are represented by rows or columns in an array; respectively combining all the question text segments with each answer text segment to constitute question-and-answer pairs; updating, according to a correlation between the words in the question text segments and the words in the answer text segments in the question-and-answer pairs, all data represented in the matrices; tiling all the updated matrices, and performing linear transformation to determine a probability of conforming to any emotion type; and taking an emotion having the highest probability as the emotion of an answerer, and storing the emotion of the answerer into a blockchain network.
EMOTION DETERMINING METHOD AND APPARATUS FOR MULTIPLE ROUNDS OF QUESTIONS AND ANSWERS, COMPUTER DEVICE, AND STORAGE MEDIUM