Olivier Parent


Fixing paper assignments

  1. Please select all papers that belong to the same person.
  2. Indicate below which author they should be assigned to.
Provide a valid ORCID iD here. This will be used to match future papers to this author.
Provide the name of the school or the university where the author has received or will receive their highest degree (e.g., Ph.D. institution for researchers, or current affiliation for students). This will be used to form the new author page ID, if needed.

TODO: "submit" and "cancel" buttons here


2022

pdf bib
SentEMO: A Multilingual Adaptive Platform for Aspect-based Sentiment and Emotion Analysis
Ellen De Geyndt | Orphee De Clercq | Cynthia Van Hee | Els Lefever | Pranaydeep Singh | Olivier Parent | Veronique Hoste
Proceedings of the 12th Workshop on Computational Approaches to Subjectivity, Sentiment & Social Media Analysis

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