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Found 14 papers, 3 papers with code
OffendES: A New Corpus in Spanish for Offensive Language Research
Offensive language detection and analysis has become a major area of research in Natural Language Processing.
SHARE: A Lexicon of Harmful Expressions by Spanish Speakers
In this paper we present SHARE, a new lexical resource with 10, 125 offensive terms and expressions collected from Spanish speakers.
Angry Men, Sad Women: Large Language Models Reflect Gendered Stereotypes in Emotion Attribution
We then analyze the emotions generated by the models in relation to the gender-event pairs.
Emotion Analysis in NLP: Trends, Gaps and Roadmap for Future Directions
We then discuss four lacunae: (1) the absence of demographic and cultural aspects does not account for the variation in how emotions are perceived, but instead assumes they are universally experienced in the same manner; (2) the poor fit of emotion categories from the two main emotion theories to the task; (3) the lack of standardized EA terminology hinders gap identification, comparison, and future goals; and (4) the absence of interdisciplinary research isolates EA from insights in other fields.
A Tale of Pronouns: Interpretability Informs Gender Bias Mitigation for Fairer Instruction-Tuned Machine Translation
In MT, this might lead to misgendered translations, resulting, among other harms, in the perpetuation of stereotypes and prejudices.
Wisdom of Instruction-Tuned Language Model Crowds. Exploring Model Label Variation
Recent studies emphasize the importance of considering human label variation in data annotation.
Natural Language Inference Prompts for Zero-shot Emotion Classification in Text across Corpora
This raises the question how to prompt a natural language inference model for zero-shot learning emotion classification.
Multi-Task Learning with Sentiment, Emotion, and Target Detection to Recognize Hate Speech and Offensive Language
The recognition of hate speech and offensive language (HOF) is commonly formulated as a classification task to decide if a text contains HOF.
SINAI at SemEval-2021 Task 5: Combining Embeddings in a BiLSTM-CRF model for Toxic Spans Detection
However, detecting toxic spans is crucial to identify why a text is toxic and can assist human moderators to locate this type of content on social media.
SINAI at SemEval-2019 Task 5: Ensemble learning to detect hate speech against inmigrants and women in English and Spanish tweets
Misogyny and xenophobia are some of the most important social problems.
SINAI at SemEval-2019 Task 3: Using affective features for emotion classification in textual conversations
Detecting emotions in textual conversation is a challenging problem in absence of nonverbal cues typically associated with emotion, like fa- cial expression or voice modulations.
SINAI at SemEval-2019 Task 6: Incorporating lexicon knowledge into SVM learning to identify and categorize offensive language in social media
Offensive language has an impact across society.
SINAI at IEST 2018: Neural Encoding of Emotional External Knowledge for Emotion Classification
In this paper, we describe our participation in WASSA 2018 Implicit Emotion Shared Task (IEST 2018).
SINAI at SemEval-2018 Task 1: Emotion Recognition in Tweets
Emotion classification is a new task that combines several disciplines including Artificial Intelligence and Psychology, although Natural Language Processing is perhaps the most challenging area.
