no code implementations • EACL (WASSA) 2021 • Luna De Bruyne, Orphee De Clercq, Veronique Hoste
The models are tested on 1, 000 Dutch tweets and 1, 000 captions from TV-shows which have been manually annotated with emotion categories and dimensions.
no code implementations • LREC 2022 • Luna De Bruyne, Akbar Karimi, Orphee De Clercq, Andrea Prati, Veronique Hoste
In this paper, we present a multimodal dataset for Aspect-Based Emotion Analysis (ABEA).
Aspect-Based Sentiment Analysis Aspect-Based Sentiment Analysis (ABSA) +3
no code implementations • LREC 2020 • Luna De Bruyne, Orphee De Clercq, Veronique Hoste
Seeing the myriad of existing emotion models, with the categorical versus dimensional opposition the most important dividing line, building an emotion-annotated corpus requires some well thought-out strategies concerning framework choice.
no code implementations • 20 Nov 2019 • Luna De Bruyne, Pepa Atanasova, Isabelle Augenstein
Emotion lexica are commonly used resources to combat data poverty in automatic emotion detection.
no code implementations • SEMEVAL 2018 • Luna De Bruyne, Orph{\'e}e De Clercq, V{\'e}ronique Hoste
This paper presents an emotion classification system for English tweets, submitted for the SemEval shared task on Affect in Tweets, subtask 5: Detecting Emotions.