@inproceedings{de-geyndt-etal-2022-sentemo,
title = "{S}ent{EMO}: A Multilingual Adaptive Platform for Aspect-based Sentiment and Emotion Analysis",
author = "De Geyndt, Ellen and
De Clercq, Orphee and
Van Hee, Cynthia and
Lefever, Els and
Singh, Pranaydeep and
Parent, Olivier and
Hoste, Veronique",
editor = "Barnes, Jeremy and
De Clercq, Orph{\'e}e and
Barriere, Valentin and
Tafreshi, Shabnam and
Alqahtani, Sawsan and
Sedoc, Jo{\~a}o and
Klinger, Roman and
Balahur, Alexandra",
booktitle = "Proceedings of the 12th Workshop on Computational Approaches to Subjectivity, Sentiment {\&} Social Media Analysis",
month = may,
year = "2022",
address = "Dublin, Ireland",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2022.wassa-1.5",
doi = "10.18653/v1/2022.wassa-1.5",
pages = "51--61",
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 dashboards, allowing companies to gain more insights into what stakeholders think of their products and services. The SentEMO platform is available at \url{https://sentemo.ugent.be}",
}
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%0 Conference Proceedings
%T SentEMO: A Multilingual Adaptive Platform for Aspect-based Sentiment and Emotion Analysis
%A De Geyndt, Ellen
%A De Clercq, Orphee
%A Van Hee, Cynthia
%A Lefever, Els
%A Singh, Pranaydeep
%A Parent, Olivier
%A Hoste, Veronique
%Y Barnes, Jeremy
%Y De Clercq, Orphée
%Y Barriere, Valentin
%Y Tafreshi, Shabnam
%Y Alqahtani, Sawsan
%Y Sedoc, João
%Y Klinger, Roman
%Y Balahur, Alexandra
%S Proceedings of the 12th Workshop on Computational Approaches to Subjectivity, Sentiment & Social Media Analysis
%D 2022
%8 May
%I Association for Computational Linguistics
%C Dublin, Ireland
%F de-geyndt-etal-2022-sentemo
%X 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 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
%R 10.18653/v1/2022.wassa-1.5
%U https://aclanthology.org/2022.wassa-1.5
%U https://doi.org/10.18653/v1/2022.wassa-1.5
%P 51-61
Markdown (Informal)
[SentEMO: A Multilingual Adaptive Platform for Aspect-based Sentiment and Emotion Analysis](https://aclanthology.org/2022.wassa-1.5) (De Geyndt et al., WASSA 2022)
ACL
- Ellen De Geyndt, Orphee De Clercq, Cynthia Van Hee, Els Lefever, Pranaydeep Singh, Olivier Parent, and Veronique Hoste. 2022. SentEMO: A Multilingual Adaptive Platform for Aspect-based Sentiment and Emotion Analysis. In Proceedings of the 12th Workshop on Computational Approaches to Subjectivity, Sentiment & Social Media Analysis, pages 51–61, Dublin, Ireland. Association for Computational Linguistics.