With advanced digitalisation, we can observe a massive increase of user-generated content
on the web that provides opinions of people on different subjects. Sentiment analysis is the …

Recently, sequential transfer learning emerged as a modern technique for applying the
“pretrain then fine-tune” paradigm to leverage existing knowledge to improve the …

Sentiment analysis, one of the research hotspots in the natural language processing field,
has attracted the attention of researchers, and research papers on the field are increasingly …

Perceptual quality assessment plays a vital role in the visual communication systems owing
to the existence of quality degradations introduced in various stages of visual signal …

Internet forums and public social media, such as online healthcare forums, provide a
convenient channel for users (people/patients) concerned about health issues to discuss …

Over the last decade Deep learning-based models surpasses classical machine learning
models in a variety of text classification tasks. The primary challenge with text classification …

This work presents and assesses the power of various volumetric, sentiment, and social
network approaches to predict crucial decisions from online social media platforms. The …

As data grow rapidly on social media by users' contributions, specially with the recent
coronavirus pandemic, the need to acquire knowledge of their behaviors is in high demand …

Limited training data is a long-standing problem for video emotion analysis (VEA). Existing
works leverage the power of large-scale image datasets for transferring while failing to …

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 …