A Review of Deep Learning Models for Twitter Sentiment Analysis: Challenges and Opportunities
Microblogging site Twitter (re-branded to X since July 2023) is one of the most influential
online social media websites, which offers a platform for the masses to communicate …
online social media websites, which offers a platform for the masses to communicate …
A novel hybrid deep learning model for detecting COVID-19-related rumors on social media based on LSTM and concatenated parallel CNNs
Spreading rumors in social media is considered under cybercrimes that affect people,
societies, and governments. For instance, some criminals create rumors and send them on …
societies, and governments. For instance, some criminals create rumors and send them on …
Leveraging the meta-embedding for text classification in a resource-constrained language
This paper proposes an intelligent text classification framework for a resource-constrained
language like Bengali, which is considered a challenging task due to the lack of standard …
language like Bengali, which is considered a challenging task due to the lack of standard …
Economy and carbon emissions optimization of different provinces or regions in China using an improved temporal attention mechanism based on gate recurrent unit
L Cao, Y Han, M Feng, Z Geng, Y Lu, L Chen… - Journal of Cleaner …, 2024 - Elsevier
With the implementation of 14th Five-Year Plan in China and the completion of the poverty
alleviation task, the economy in China has made great progress. However, the carbon …
alleviation task, the economy in China has made great progress. However, the carbon …
TextGuise: Adaptive adversarial example attacks on text classification model
Adversarial examples greatly compromise the security of deep learning models. The key to
improving the robustness of a natural language processing (NLP) model is to study attacks …
improving the robustness of a natural language processing (NLP) model is to study attacks …
Sentiment and attention of the Chinese public toward electric vehicles: A big data analytics approach
Q Qin, Z Zhou, J Zhou, Z Huang, X Zeng… - Engineering Applications of …, 2024 - Elsevier
Individuals' attention and sentiment are the keys to adopting electric vehicles (EVs).
Traditional questionnaires and interviews cannot fully and accurately reflect the attention …
Traditional questionnaires and interviews cannot fully and accurately reflect the attention …
A user review data-driven supplier ranking model using aspect-based sentiment analysis and fuzzy theory
Background: The supplier selection problem is a sophisticated decision-making process that
involves evaluating multiple factors. While previous research has primarily focused on …
involves evaluating multiple factors. While previous research has primarily focused on …
Big data-assisted urban governance: forecasting social events with a periodicity by employing different time series algorithms
Z Zhang, X Lin, S Shan, Z Yin - Library Hi Tech, 2024 - emerald.com
Purpose This study aims to analyze government hotline text data and generating forecasts
could enable the effective detection of public demands and help government departments …
could enable the effective detection of public demands and help government departments …
[HTML][HTML] Enhanced joint hybrid deep neural network explainable artificial intelligence model for 1-hr ahead solar ultraviolet index prediction
Abstract Background and Objective Exposure to solar ultraviolet (UV) radiation can cause
malignant keratinocyte cancer and eye disease. Developing a user-friendly, portable, real …
malignant keratinocyte cancer and eye disease. Developing a user-friendly, portable, real …
Dynamic impact of negative public sentiment on agricultural product prices during COVID-19
Y Liu, S Liu, D Ye, H Tang, F Wang - Journal of retailing and consumer …, 2022 - Elsevier
The COVID-19 pandemic has had a significantly negative impact on public sentiment, which
has resulted in panic and some irrational buying behavior, which in turn has had a complex …
has resulted in panic and some irrational buying behavior, which in turn has had a complex …