Twitter sentiment detectors (TSDs) provide a better solution to evaluate the quality of service
and product than other traditional technologies. The classification accuracy and detection …

Sharing short reviews on Social Networking Sites has contributed to rising textual data. For
this short review text, needed a text classification model to identify short texts, organize them …

Due to the increasing growth of social media content on websites such as Twitter and
Facebook, analyzing textual sentiment has become a challenging task. Therefore, many …

The exponential progress in technology and the internet has resulted in an unparalleled
surge in online engagement, where individuals openly express their viewpoints. Users …

The estimation of reliability and remaining useful life (RUL) for a gear pair plays a critical
role in ensuring its proper functioning and maintenance. The work focuses on designing a …

Arabic hateful speech recognition has long been a major area of focus in Natural Language
Processing (NLP) research. In light of recent advancements in transformer models and deep …

The curse of high dimensionality in text classification is a worrisome problem that requires
efficient and optimal feature selection (FS) methods to improve classification accuracy and …

This study proposes a novel text classification model, MBConv-CapsNet, to address large-
scale text data classification issues in the Internet era. Integrating the advantages of Mobile …

Regular expression (regex) based automated qualitative coding helps reduce researchers'
effort in manually coding text data, without sacrificing transparency of the coding process …

Feature selection is an essential step in text classification tasks to enhance model
performance, reduce computational complexity, and mitigate the risk of overfitting. Filter …