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Found 19 papers, 2 papers with code
Identifying professions & occupations in Health-related Social Media using Natural Language Processing
This paper describes the entry of the research group SINAI at SMM4H’s ProfNER task on the identification of professions and occupations in social media related with health.
TANDO: A Corpus for Document-level Machine Translation
Document-level Neural Machine Translation aims to increase the quality of neural translation models by taking into account contextual information.
SINAI at SemEval-2020 Task 12: Offensive Language Identification Exploring Transfer Learning Models
This paper describes the participation of SINAI team at Task 12: OffensEval 2: Multilingual Offensive Language Identification in Social Media.
EmoEvent: A Multilingual Emotion Corpus based on different Events
We report some linguistic statistics about the data set in order to observe the difference between English and Spanish speakers when they express emotions related to the same events.
Transfer learning applied to text classification in Spanish radiological reports
In this study we show a system using specific radiology clinic codes.
Using Snomed to recognize and index chemical and drug mentions.
In this paper we describe a new named entity extraction system.
Detecting Anorexia in Spanish Tweets
In order to validate the effectiveness of the SAD corpus, we also propose several machine learning approaches for automatically detecting anorexia symptoms in the corpus.
Using Machine Learning and Deep Learning Methods to Find Mentions of Adverse Drug Reactions in Social Media
Over time the use of social networks is becoming very popular platforms for sharing health related information.
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 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 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).
A review of Spanish corpora annotated with negation
The availability of corpora annotated with negation information is essential to develop negation processing systems in any language.
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.
SINAI at SemEval-2017 Task 4: User based classification
This document describes our participation in SemEval-2017 Task 4: Sentiment Analysis in Twitter.
Problematic Cases in the Annotation of Negation in Spanish
This paper presents the main sources of disagreement found during the annotation of the Spanish SFU Review Corpus with negation (SFU ReviewSP -NEG).
