I2RNTU at SemEval-2016 Task 4: Classifier Fusion for Polarity Classification in Twitter

ej-sa-2017 at SemEval-2017 Task 4: Experiments for Target oriented Sentiment Analysis in Twitter

This paper describes the system we have used for participating in Subtasks A (Message Polarity Classification) and B (Topic-Based Message Polarity Classification according to a two-point scale) of SemEval-2017 Task 4 Sen…

SENSEI-LIF at SemEval-2016 Task 4: Polarity embedding fusion for robust sentiment analysis

NileTMRG at SemEval-2017 Task 4: Arabic Sentiment Analysis

This paper describes two systems that were used by the authors for addressing Arabic Sentiment Analysis as part of SemEval-2017, task 4. The authors participated in three Arabic related subtasks which are: Subtask A (Mes…

BrainEE at SemEval-2019 Task 3: Ensembling Linear Classifiers for Emotion Prediction

The paper describes an ensemble of linear perceptrons trained for emotion classification as part of the SemEval-2019 shared-task 3. The model uses a matrix of probabilities to weight the activations of the base-classifie…

Tweester at SemEval-2017 Task 4: Fusion of Semantic-Affective and pairwise classification models for sentiment analysis in Twitter

In this paper, we describe our submission to SemEval2017 Task 4: Sentiment Analysis in Twitter. Specifically the proposed system participated both to tweet polarity classification (two-, three- and five class) and tweet …