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 …

Drug-resistant tuberculosis is a substantial health-care concern worldwide. Despite culture-
based methods being considered the gold standard for drug susceptibility testing, molecular …

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 …

Aspect level sentiment analysis is a fine-grained task in sentiment analysis. It extracts
aspects and their corresponding sentiment polarity from opinionated text. The first subtask of …

Sentiment analysis aims to automatically classify the subject's sentiment (eg, positive,
negative, or neutral) towards a particular aspect such as a topic, product, movie, news, etc …

Information about artificial intelligence generated content (AIGC) has attracted great
attention from the public. ChatGPT has gained attention from many countries due to its …

Sentiment analysis automatically evaluates people's opinions of products or services. It is an
emerging research area with promising advancements in high-resource languages such as …

We study the selection of transfer languages for different Natural Language Processing
tasks, specifically sentiment analysis, named entity recognition and dependency parsing. In …

Large pre-trained language models (LMs) have demonstrated the ability to obtain good
performance on downstream tasks with limited examples in cross-lingual settings. However …

We study the selection of transfer languages for automatic abusive language detection.
Instead of preparing a dataset for every language, we demonstrate the effectiveness of cross …