The analysis of the opinions of customers and users has been always of great interest in
supporting decision-making in many fields, especially in marketing. Sentiment analysis (SA) …

Sentiment analysis in conversations has gained increasing attention in recent years for the
growing amount of applications it can serve, eg, sentiment analysis, recommender systems …

Multimodal emotion recognition has gained traction in affective computing research
community to overcome the limitations posed by the processing a single form of data and to …

Sarcasm is a complicated linguistic term commonly found in e-commerce and social media
sites. Failure to identify sarcastic utterances in Natural Language Processing applications …

Traditional methods for sentiment analysis, when applied in a monolingual context, often
yield less than optimal results in multilingual settings. This underscores the need for a more …

This paper investigates the ability of multilingual BERT (mBERT) language model to transfer
syntactic knowledge cross-lingually, verifying if and to which extent syntactic dependency …

QuaPy is an open-source framework for performing quantification (aka supervised
prevalence estimation), written in Python. Quantification is the task of training quantifiers via …

The dramatic growth of the Web has motivated researchers to extract knowledge from
enormous repositories and to exploit the knowledge in myriad applications. In this study, we …

Sentiment Quantification aims to detect the overall sentiment polarity of users from a set of
reviews corresponding to a target. Existing methods equally treat and aggregate individual …

This open access book provides an introduction and an overview of learning to quantify (aka
“quantification”), ie the task of training estimators of class proportions in unlabeled data by …