Twenty-four studies on twenty-three distinct languages and eleven social media illustrate the
steady interest in deep learning approaches for multilingual sentiment analysis of social …

The rapid growth of e-commerce has significantly increased the demand for advanced
techniques to address specific tasks in the e-commerce field. In this paper, we present a …

The pandemic has taken the world by storm. Almost the entire world went into lockdown to
save the people from the deadly COVID-19. Scientists around the around have come up with …

Real-time market prediction tool tracking public opinion in specialized newsgroups and
informative market data persuades investors of financial markets. Previous works mainly …

Zigzag conversational patterns of contents in social media are often perceived as noisy or
informal text. Unrestricted usage of vocabulary in social media communications complicates …

Aspect-based sentiment analysis (ABSA) is currently among the most vigorous areas in
natural language processing (NLP). Individuals, private and government institutions are …

Technology and ride-sharing services have become more accessible and convenient as a
result of the growth of the Internet. Passengers increasingly focus on digital reviews to help …

Despite intensive efforts to prevent and control malicious human activities, they still pose
grave risks and significant challenges in cyber-space. Malicious human activities are an …

Promoting healthy discourse on community-based online platforms like Reddit can be
challenging, especially when conversations show ominous signs of toxicity. Therefore, in …

Purpose Neural network (NN)-based deep learning (DL) approach is considered for
sentiment analysis (SA) by incorporating convolutional neural network (CNN), bi-directional …