AE-CharCNN: Char-Level Convolutional Neural Networks for Aspect-Based Sentiment Analysis

Sentiment Analysis was developed to support individuals in the harsh task of obtaining significant information from large amounts of non-structured opinionated data sources, such as social networks and specialized reviews websites. A yet more challenging task is to point out which part of the target entity is addressed in the opinion. This task is called Aspect-Based Sentiment Analysis. The majority of work focuses on coping with English text in the literature, but other languages lack resources, tools, and techniques. This paper focuses on Aspect-Based Sentiment Analysis for Accommodation Services Reviews written in Brazilian Portuguese. Our proposed approach uses Convolution Neural Networks with inputs in Character-level. Results suggest that our approach outperforms lexicon-based and LSTM-based approaches, displaying state-of-the-art performance for binary Aspect-Based Sentiment Analysis.