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Found 7 papers, 1 papers with code
HurtBERT: Incorporating Lexical Features with BERT for the Detection of Abusive Language
The detection of abusive or offensive remarks in social texts has received significant attention in research.
Data Augmentation for Emotion Detection in Small Imbalanced Text Data
Our experimental results show that using the augmented data when training the classifier model leads to significant improvements.
Deep Learning for Opinion Mining and Topic Classification of Course Reviews
Student opinions for a course are important to educators and administrators, regardless of the type of the course or the institution.
Automatically Classifying Emotions based on Text: A Comparative Exploration of Different Datasets
Emotion Classification based on text is a task with many applications which has received growing interest in recent years.
FlorUniTo@TRAC-2: Retrofitting Word Embeddings on an Abusive Lexicon for Aggressive Language Detection
This paper describes our participation to the TRAC-2 Shared Tasks on Aggression Identification.
Lexicon-Enhancement of Embedding-based Approaches Towards the Detection of Abusive Language
The methods implemented and experimented with in this paper are quite different from each other, not only in the type of lexicons they use (sentiment or semantic), but also in the way they use the knowledge from the lexicons, in order to construct or to change embeddings that are ultimately fed into the learning model.
Exploring the Use of Lexicons to aid Deep Learning towards the Detection of Abusive Language
Detecting abusive language is a significant research topic, which has received a lot of attention recently.
