The selection of word embedding and deep learning models for better outcomes is vital.
Word embeddings are an n-dimensional distributed representation of a text that attempts to …

Abstract Foundation and Large Language Models (FLLMs) are models that are trained using
a massive amount of data with the intent to perform a variety of downstream tasks. FLLMs …

Sentiment analysis has been a well-studied research direction in computational linguistics.
Deep neural network models, including convolutional neural networks (CNN) and recurrent …

Sentiment analysis has been a hot research topic in natural language processing and data
mining fields in the last decade. Recently, deep neural network (DNN) models are being …

Sentiment analysis is one of the major tasks of natural language processing, in which
attitudes, thoughts, opinions, or judgments toward a particular subject has been extracted …

Financial and economic news is continuously monitored by financial market participants.
According to the efficient market hypothesis, all past information is reflected in stock prices …

Massive open online courses (MOOCs) are recent innovative approaches in distance
education, which provide learning content to participants without age‐, gender‐, race‐, or …

Sentiment analysis (SA) is a widely used contextual mining technique for extracting useful
and subjective information from text-based data. It applies on Natural Language Processing …

Topic extraction is an essential task in bibliometric data analysis, data mining and
knowledge discovery, which seeks to identify significant topics from text collections. The …

With the widespread use of social networks, blogs, forums and e-commerce web sites, the
volume of user generated textual data is growing exponentially. User opinions in product …