A Hybrid Deep Learning System of CNN and LRCN to Detect Cyberbullying from SNS Comments

Abstract

The cyberbullying is becoming a significant social issue, in proportion to the proliferation of Social Network Service (SNS). The cyberbullying commentaries can be categorized into syntactic and semantic subsets. In this paper, we propose an ensemble method of the two deep learning models: One is character-level CNN which captures low-level syntactic information from the sequence of characters and is robust to noise using the transfer learning. The other is word-level LRCN which captures high-level semantic information from the sequence of words, complementing the CNN model. Empirical results show that the performance of the ensemble method is significantly enhanced, outperforming the state-of-the-art methods for detecting cyberbullying comment. The model is analyzed by t-SNE algorithm to investigate the mutually cooperative relations between syntactic and semantic models.