Sentiment analysis on public opinion expressed in social networks, such as Twitter or
Facebook, has been developed into a wide range of applications, but there are still many …

Today, almost all active organizations manage a large amount of data from their business
operations with partners, customers, and even competitors. They rely on Data Value Chain …

The growing interest in Big Data (BD) and Big Data Analytics (BDA) by the business in
recent years requires looking for models to reveal their economic potential and their ability to …

ABSTRACT The Black Friday event has become a global opportunity for marketing and
companies' strategies aimed at increasing sales. The present study aims to understand …

Sentiment analysis is an ongoing research field within the discipline of data mining. The
majority of academics employ deep learning models for sentiment analysis due to their …

(1) Background: in early 2020, COVID-19 broke out. Driven by people's psychology of
conformity, panic, group polarization, etc., various rumors appeared and spread wildly, and …

Most of the previous studies on the semantic analysis of social media feeds have not
considered the issue of ambiguity that is associated with slangs, abbreviations, and …

This study describes a hybrid semantic knowledgebase-machine learning strategy for
mining domain feature-level opinions and categorizing them on a multi-point scale. A …

An immense volume of user-generated content exists online due to the exponential growth
of internet usage among individuals. However, this abundance presents substantial …

Sentiment analysis is helpful to bestow ability of understanding human's attitude in texts on
artificial intelligence systems. In this area, text sentiment is usually signaled by a few …