Neural networks : the official journal of the International Neural Network Society
Sep 20, 2022
In this paper, we study the multi-task sentiment classification problem in the continual learning setting, i.e., a model is sequentially trained to classify the sentiment of reviews of products in a particular category. The use of common sentiment wo...
Multimodal sentiment analysis is an essential task in natural language processing which refers to the fact that machines can analyze and recognize emotions through logical reasoning and mathematical operations after learning multimodal emotional feat...
Computational intelligence and neuroscience
Sep 8, 2022
Weibo platform is an indispensable transmission channel in education policy release and dissemination. The events and sentiments contained in education policies microblogs include the public sentiment and support the general management and guidance s...
IEEE transactions on neural networks and learning systems
Aug 31, 2022
Long short-term memory (LSTM) neural networks and attention mechanism have been widely used in sentiment representation learning and detection of texts. However, most of the existing deep learning models for text sentiment analysis ignore emotion's m...
The study of understanding sentiment and emotion in speech is a challenging task in human multimodal language. However, in certain cases, such as telephone calls, only audio data can be obtained. In this study, we independently evaluated sentiment an...
Mission statements (henceforth: missions) are strategic planning communication tools used by all types of organizations worldwide. Missions communicate an organization's purpose, values, standards, and strategy. Research on missions has been prolific...
Computational intelligence and neuroscience
Aug 9, 2022
Multimodal sentiment analysis has been an active subfield in natural language processing. This makes multimodal sentiment tasks challenging due to the use of different sources for predicting a speaker's sentiment. Previous research has focused on ext...
Computational intelligence and neuroscience
Jul 31, 2022
Latent Dirichlet Allocation (LDA) is an approach to unsupervised learning that aims to investigate the semantics among words in a document as well as the influence of a subject on a word. As an LDA-based model, Joint Sentiment-Topic (JST) examines th...