AspectEmo: Multi-Domain Corpus of Consumer Reviews for Aspect-Based Sentiment Analysis
Jan Kocoń, Jarema Radom, Ewa Kaczmarz-Wawryk, Kamil Wabnic, Ada Zajaczkowska, Monika Zaśko-Zielińska · 2021 International Conference on Data Mining Workshops (ICDMW) · 2021
Aspect-based sentiment analysis (ABSA) is a text analysis method that categorizes data by aspects and identifies the sentiment assigned to each aspect. Aspect-based sentiment analysis can be used to analyze customer opinions by associating specific sentiments with different aspects of a product or service. Most of the work in this topic is thoroughly performed for English, but many low-resource languages still lack adequate annotated data to create automatic methods for the ABSA task. In this work, we present annotation guidelines for the ABSA task for Polish and preliminary annotation results in the form of the AspectEmo corpus, containing over 1.5k consumer reviews annotated with over 63k annotations. We present an agreement analysis on the resulting annotated corpus and preliminary results using transformer-based models trained on AspectEmo.