Kersting

In this study, we present an approach and a dataset for aspect-based sentiment analysis, showing how we extract and classify aspect phrases. The research field of aspect-based sentiment analysis aims at finding opinions expressed for individual characteristics of products or services in natural language texts. In the literature, reviews for common products or services such as smartphones or restaurants were mostly investigated. We describe our newly annotated dataset of German physician reviews, which presents a sensitive and linguistically complex domain, taking care to describe the annotation process and the functionality of our neural network approach. Finally, we introduce a model that can extract and classify aspect phrases in one step while obtaining an F1 score of 80%.