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Sentiment Analysis

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Deep Neural Networks Applied to Stock Market Sentiment Analysis.

Sensors (Basel, Switzerland)
The volume of data is growing exponentially and becoming more valuable to organizations that collect it, from e-commerce data, shipping, audio and video logs, text messages, internet search queries, stock market activity, financial transactions, the ...

Transfer Learning for Sentiment Analysis Using BERT Based Supervised Fine-Tuning.

Sensors (Basel, Switzerland)
The growth of the Internet has expanded the amount of data expressed by users across multiple platforms. The availability of these different worldviews and individuals' emotions empowers sentiment analysis. However, sentiment analysis becomes even mo...

Developing an Intelligent System with Deep Learning Algorithms for Sentiment Analysis of E-Commerce Product Reviews.

Computational intelligence and neuroscience
Most consumers rely on online reviews when deciding to purchase e-commerce services or products. Unfortunately, the main problem of these reviews, which is not completely tackled, is the existence of deceptive reviews. The novelty of the proposed sys...

Research on Brand Image Evaluation Method Based on Consumer Sentiment Analysis.

Computational intelligence and neuroscience
Brand image assessment is a key step to reasonably quantify the value of a brand and has far-reaching significance for improving the competitiveness of an enterprise. With the rapid development of Internet technology, traditional questionnaires can n...

Utilization of sentiment analysis to assess and compare negative finding reporting in veterinary and human literature.

Research in veterinary science
Publication bias and the decreased publication of trials with negative or non-significant results is a well-recognized problem in human and veterinary medical publications. These biases may present an incomplete picture of evidence-based clinical car...

Two-Level LSTM for Sentiment Analysis With Lexicon Embedding and Polar Flipping.

IEEE transactions on cybernetics
Sentiment analysis is a key component in various text mining applications. Numerous sentiment classification techniques, including conventional and deep-learning-based methods, have been proposed in the literature. In most existing methods, a high-qu...

Heterogeneous Ensemble Deep Learning Model for Enhanced Arabic Sentiment Analysis.

Sensors (Basel, Switzerland)
Sentiment analysis was nominated as a hot research topic a decade ago for its increasing importance in analyzing the people's opinions extracted from social media platforms. Although the Arabic language has a significant share of the content shared a...

Aspect Based Twitter Sentiment Analysis on Vaccination and Vaccine Types in COVID-19 Pandemic With Deep Learning.

IEEE journal of biomedical and health informatics
Due to the COVID-19 pandemic, vaccine development and community vaccination studies are carried out all over the world. At this stage, the opposition to the vaccine seen in the society or the lack of trust in the developed vaccine is an important fac...

An Improved BERT and Syntactic Dependency Representation Model for Sentiment Analysis.

Computational intelligence and neuroscience
Text representation of social media is an important task for users' sentiment analysis. Utilizing the better representation, we can accurately acquire the real semantic information expressed by online users. However, existing works cannot achieve the...

Real-Time Twitter Spam Detection and Sentiment Analysis using Machine Learning and Deep Learning Techniques.

Computational intelligence and neuroscience
In this modern world, we are accustomed to a constant stream of data. Major social media sites like Twitter, Facebook, or Quora face a huge dilemma as a lot of these sites fall victim to spam accounts. These accounts are made to trap unsuspecting gen...