In machine learning, two approaches outperform traditional algorithms: ensemble learning
and deep learning. The former refers to methods that integrate multiple base models in the …

Social Media (SM) are the most widespread and rapid data generation applications on the
Internet increase the study of these data. However, the efficient processing of such massive …

Background: Few-shot learning (FSL) is a class of machine learning methods that require
small numbers of labeled instances for training. With many medical topics having limited …

This paper describes the fifth year of the Sentiment Analysis in Twitter task. SemEval-2017
Task 4 continues with a rerun of the subtasks of SemEval-2016 Task 4, which include …

Words often convey affect--emotions, feelings, and attitudes. Further, different words can
convey affect to various degrees (intensities). However, existing manually created lexicons …

This paper discusses the fourth year of the``Sentiment Analysis in Twitter Task''. SemEval-
2016 Task 4 comprises five subtasks, three of which represent a significant departure from …

We propose a new task in the field of computational argumentation in which we investigate
qualitative properties of Web arguments, namely their convincingness. We cast the problem …

Sentiment analysis, commonly known as “opinion mining,” aims to identify sentiment
polarities in opinion texts. Recent years have seen a significant increase in the acceptance …

In recent years, some methods of sentiment analysis have been developed for the health
domain; however, the diabetes domain has not been explored yet. In addition, there is a lack …

We study in this work the importance of depth in convolutional models for text classification,
either when character or word inputs are considered. We show on 5 standard text …