Sentiments or opinions from social media provide the most up-to-date and inclusive
information, due to the proliferation of social media and the low barrier for posting the …

As the prevalence of social media on the Internet, opinion mining has become an essential
approach to analyzing so many data. Various applications appear in a wide range of …

Semi-supervised learning is the branch of machine learning concerned with using labelled
as well as unlabelled data to perform certain learning tasks. Conceptually situated between …

Deep learning has led to tremendous progress in the field of medical artificial intelligence.
However, training deep-learning models usually require large amounts of annotated data …

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 …

It is important to apply models trained on a large number of labeled samples to different
domains because collecting many labeled samples in various domains is expensive. To …

Semantic processing is a fundamental research domain in computational linguistics. In the
era of powerful pre-trained language models and large language models, the advancement …

Sentiment Analysis (SA) is an ongoing field of research in text mining field. SA is the
computational treatment of opinions, sentiments and subjectivity of text. This survey paper …

In recent years, a great many methods of learning from multi-view data by considering the
diversity of different views have been proposed. These views may be obtained from multiple …

Sentiment analysis and opinion mining is the field of study that analyzes people's opinions,
sentiments, evaluations, attitudes, and emotions from written language. It is one of the most …