Sentiment analysis using deep learning approaches: an overview
Nowadays, with the increasing number of Web 2.0 tools, users generate huge amounts of
data in an enormous and dynamic way. In this regard, the sentiment analysis appeared to be …
data in an enormous and dynamic way. In this regard, the sentiment analysis appeared to be …
Deep learning for Arabic subjective sentiment analysis: Challenges and research opportunities
The fields of machine learning and Web technologies have witnessed significant
development in the last years. This caused a ceaseless and rapid growth in sharing of the …
development in the last years. This caused a ceaseless and rapid growth in sharing of the …
{INFaaS}: Automated model-less inference serving
Despite existing work in machine learning inference serving, ease-of-use and cost efficiency
remain challenges at large scales. Developers must manually search through thousands of …
remain challenges at large scales. Developers must manually search through thousands of …
Machine learning and deep learning for sentiment analysis across languages: A survey
EM Mercha, H Benbrahim - Neurocomputing, 2023 - Elsevier
The inception and rapid growth of the Web, social media, and other online forums have
resulted in the continuous and rapid generation of opinionated textual data. Several real …
resulted in the continuous and rapid generation of opinionated textual data. Several real …
Transfer learning and sentiment analysis of Bahraini dialects sequential text data using multilingual deep learning approach
Sentiment analysis is a crucial Natural Language Processing task to analyze the user's
emotions and opinions towards events, entities, services, or products. Arabic NLP faces …
emotions and opinions towards events, entities, services, or products. Arabic NLP faces …
MiMuSA—mimicking human language understanding for fine-grained multi-class sentiment analysis
Sentiment analysis is an important natural language processing (NLP) task due to a wide
range of applications. Most existing sentiment analysis techniques are limited to the analysis …
range of applications. Most existing sentiment analysis techniques are limited to the analysis …
Gpt-4v (ision) as a social media analysis engine
Recent research has offered insights into the extraordinary capabilities of Large Multimodal
Models (LMMs) in various general vision and language tasks. There is growing interest in …
Models (LMMs) in various general vision and language tasks. There is growing interest in …
Predicting the pandemic: sentiment evaluation and predictive analysis from large-scale tweets on Covid-19 by deep convolutional neural network
Engaging deep neural networks for textual sentiment analysis is an extensively practiced
domain of research. Textual sentiment classification harnesses the full computational …
domain of research. Textual sentiment classification harnesses the full computational …
Arabicdialects: An efficient framework for arabic dialects opinion mining on twitter using optimized deep neural networks
The rapid development of tools for communication such as social networks, tweeting and
Whatsapp has generated a large mass of important textual data. Also, the COVID-19 …
Whatsapp has generated a large mass of important textual data. Also, the COVID-19 …
A semi-supervised approach for sentiment analysis of arab (ic+ izi) messages: Application to the algerian dialect
In this paper, we propose a semi-supervised approach for sentiment analysis of Arabic and
its dialects. This approach is based on a sentiment corpus, constructed automatically and …
its dialects. This approach is based on a sentiment corpus, constructed automatically and …