Application of genetic algorithm in text sentiment classification

Abstract:

In this paper, we use Sina Weibo text as the main experimental dataset, and propose a coding method suitable for selfoptimization of convolutional neural networks. Our coding method encodes each CNN framework using a hybrid double nonnumeric encoding by treating each layer as a chromosome and the parameters in each layer as a gene segment respectively, and selection, crossover and mutation algorithms are devised for CNN networks. We also propose a genetic algorithm based on sentiment analysis algorithm (GACNN) which combines genetic algorithm (GA) with convolutional neural network. The experiment and comparative analysis of GACNN and traditional algorithms demonstrates the selfoptimization of our method.