Public opinion comments are important for the public to express their emotions and demands. Accordingly, identifying the public emotions contained in comments and taking corresponding countermeasures according to the changes in the emotions are of gr...
The escalating scale and psychological harm of cyberbullying across digital platforms present a critical social challenge, demanding the urgent development of highly accurate and reliable automated detection systems. Standard fine-tuned transformer m...
Depression, stress, and anxiety are mental health disorders that are increasingly becoming a huge challenge in the digital age; at the same time, it is critical that they are detected early. Social media is a rich and complex source of emotional expr...
Emotion recognition plays an increasingly important role in today’s society and has a high social value. However, current emotion recognition technology faces the problems of insufficient feature extraction and imbalanced samples when processin...
Named entity recognition (NER) is a crucial step in building knowledge graphs for crop diseases and pests. To enhance NER accuracy, we propose a new NER model—GatedMan—based on the gated fusion unit and Manhattan attention. GatedMan utili...
The rapid growth of user-generated content in the digital space has increased the necessity of properly and interpretively analyzing sentiment and emotion systems. This research paper presents a new hybrid model, HAM (Hybrid Attention-based Model), a...
Diseases and pests have a significant impact on rice production, affecting both yield and quality. Therefore, their effective management and control are crucial for successful rice cultivation. However, current research based on rice diseases and pes...
This study addresses a lexical ambiguity issue in Sesotho sa Leboa that arises from terms with various meanings, often known as homonyms or polysemous words. When compared to, for instance, European languages, this lexical ambiguity in Sesotho sa Leb...
Aspect-based sentiment classification (ABSC) is an important task in natural language processing (NLP) that aims to predict the sentiment polarity of different aspects in a sentence. The attention mechanism and pre-trained models are commonly used in...
The increasing use of Arabic and Urdu on social media platforms, particularly Twitter, has created a growing need for robust Named Entity Recognition (NER) systems capable of handling noisy, informal, and code-mixed content. However, both languages r...
In recent years, with the increasing complexity of air traffic management and the rapid development of automation technology, efficiently and accurately extracting key information from large volumes of air traffic control (ATC) instructions has becom...