As mental health (MH) disorders become increasingly prevalent, their multifaceted
symptoms and comorbidities with other conditions introduce complexity to diagnosis, posing …

Twenty-four studies on twenty-three distinct languages and eleven social media illustrate the
steady interest in deep learning approaches for multilingual sentiment analysis of social …

The inception and rapid growth of the Web, social media, and other online forums have
resulted in the continuous and rapid generation of opinionated textual data. Several real …

Emotions are expressed in nuanced ways, which varies by collective or individual
experiences, knowledge, and beliefs. Therefore, to understand emotion, as conveyed …

Sentiment analysis aims to automatically uncover the underlying attitude that we hold
towards an entity. The aggregation of these sentiment over a population represents opinion …

Sentiment analysis is a fast growing area of research in natural language processing (NLP)
and text classifications. This technique has become an essential part of a wide range of …

We analyze the impact of sentiment and attention variables on the stock market volatility by
using a novel and extensive dataset that combines social media, news articles, information …

During the last decade, hateful and sexist content towards women is being increasingly
spread on social networks. The exposure to sexist speech has serious consequences to …

As the number of textual data is exponentially increasing, it becomes more important to
develop models to analyze the text data automatically. The texts may contain various labels …

In recent years, online shop** has surged in popularity, with customer reviews becoming
a crucial aspect of the decision-making process. Reviews not only help potential customers …