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SentEMO : a multilingual adaptive platform for aspect-based sentiment and emotion analysis

Publication type
P1
Publication status
Published
Authors
De Geyndt, E., De Clercq, O., Van Hee, C., Lefever, E., Singh, P., Parent, O., & Hoste, V.
Editor
Jeremy Barnes, Orphée De Clercq, Valentin Barriere, Shabnam Tafreshi, Sawsan Alqahtani, João Sedoc, Roman Klinger and Alexandra Balahur
Series
Proceedings of the 12th Workshop on Computational Approaches to Subjectivity, Sentiment & Social Media Analysis
Pagination
51-61
Publisher
Association for Computational Linguistics (ACL)
Conference
12th Workshop on Computational Approaches to Subjectivity, Sentiment & Social Media Analysis, collocated with ACL 2022 (WASSA 2022) (Dublin, Ireland)
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Abstract

In this paper, we present the SentEMO platform, a tool that provides aspect-based sentiment analysis and emotion detection of unstructured text data such as reviews, emails and customer care conversations. Currently, models have been trained for five domains and one general domain and are implemented in a pipeline approach, where the output of one model serves as the input for the next. The results are presented in three interactive dashboards, allowing companies to gain more insights into what stakeholders think of their products and services. The SentEMO platform is available at https://sentemo.ugent.be/(1).