Affective computing has an unprecedented potential to change the way humans interact with
technology. While the last decades have witnessed vast progress in the field, multimodal …

Sentiment Analysis is a method to identify, extract, and quantify people's feelings, opinions,
or attitudes. The wealth of online data motivates organizations to keep tabs on customers' …

Sentiment Analysis is a task of computationally recognizing and contextualizing opinions
stated in a text. We mainly assess whether the writer's attitude towards a specific topic, or a …

After its inception, emotion recognition or affective computing has increasingly become an
active research topic due to its broad applications. The corresponding computational models …

In this work, we propose BERT-WMAL, a hybrid model that brings together information
coming from data through the recent transformer deep learning model and those obtained …

Relation extraction aims at identifying semantic relations between pairs of named entities
from unstructured texts and is considered an essential prerequisite for many downstream …

The analysis of sentiments and mining of opinions have become more and more important
in years because of the development of social media technologies. The methods that utilize …

Social media analytics have proven valuable in numerous research areas as a pragmatic
tool for public opinion mining and analysis [1]. Sentiment analysis addresses the dynamics …

Flexible assembly systems are difficult to fully automate, so humans are crucial to add
flexibility to the system. Human–robot collaboration (HRC) enables the two parties to …

Aspect sentiment triplet extraction (ASTE) is a popular subtask related to aspect-based
sentiment analysis (ABSA). It extracts aspects and their associated opinion expressions and …