Effect of negation in sentences on sentiment analysis and polarity detection
P Mukherjee, Y Badr, S Doppalapudi… - Procedia Computer …, 2021 - Elsevier
Sentiment analysis is one of the sub-domains of Natural Language Processing (NLP) that is
of piqued interest in the research community. With the advent of e-commerce and social …
of piqued interest in the research community. With the advent of e-commerce and social …
Sentiment analysis of amazon product reviews using hybrid rule-based approach
A Dadhich, B Thankachan - … in Computing: Proceedings of SSIC 2021, 2022 - Springer
In the past few years, retail market industries have taken a broad form to sell the products
online and also to give the opportunity to customers to provide their valuable feedbacks …
online and also to give the opportunity to customers to provide their valuable feedbacks …
Sentiment analysis on youtube social media using decision tree and random forest algorithm: A case study
M Aufar, R Andreswari… - … Conference on Data …, 2020 - ieeexplore.ieee.org
People often gives opinions and thoughts on Social Media. Social media invites anyone
who is interested to participate by giving feedback openly, giving comments, and sharing …
who is interested to participate by giving feedback openly, giving comments, and sharing …
Reduction in data imbalance for client-side training in federated learning for the prediction of stock market prices
The approach of federated learning (FL) addresses significant challenges, including access
rights, privacy, security, and the availability of diverse data. However, edge devices produce …
rights, privacy, security, and the availability of diverse data. However, edge devices produce …
Conglomeration of deep neural network and quantum learning for object detection: Status quo review
PK Sinha, R Marimuthu - Knowledge-Based Systems, 2024 - Elsevier
The practice of deep neural framework specific to convolutional neural networks
(ConNeuNets) in domain of object detection is substantial. The existing deep ConNeuNets …
(ConNeuNets) in domain of object detection is substantial. The existing deep ConNeuNets …
Multinomial naive bayesian classifier framework for systematic analysis of smart iot devices
Businesses need to use sentiment analysis, powered by artificial intelligence and machine
learning to forecast accurately whether or not consumers are satisfied with their offerings …
learning to forecast accurately whether or not consumers are satisfied with their offerings …
Multi-aspect oriented sentiment classification: prior knowledge topic modelling and ensemble learning classifier approach
N AlGhamdi, S Khatoon, M Alshamari - Applied Sciences, 2022 - mdpi.com
User-generated content on numerous sites is indicative of users' sentiment towards many
issues, from daily food intake to using new products. Amid the active usage of social …
issues, from daily food intake to using new products. Amid the active usage of social …
Mining of customer review feedback using sentiment analysis for smart phone product
P Suresh, K Gurumoorthy - International Conference on Computing …, 2022 - Springer
With the fast growth of e-commerce, a large number of products are sold online, and a lot
more people are purchasing products online. People also give feedback of product …
more people are purchasing products online. People also give feedback of product …
[PDF][PDF] Zavira at HOPE2023@ IberLEF: Hope Speech Detection from Text using TF-IDF Features and Machine Learning Algorithms.
This paper presents the results of our participation in the shared task Multilingual Hope
Speech detection aimed at classifying texts into hope and non-hope categories. The task …
Speech detection aimed at classifying texts into hope and non-hope categories. The task …
Sentiment analysis on Twitter data: comparative study on different approaches
Social media has become incredibly popular these days for communicating with friends and
for sharing opinions. According to current statistics, almost 2.22 billion people use social …
for sharing opinions. According to current statistics, almost 2.22 billion people use social …