Sentiment analysis using deep learning architectures: a review
A Yadav, DK Vishwakarma - Artificial Intelligence Review, 2020 - Springer
Social media is a powerful source of communication among people to share their sentiments
in the form of opinions and views about any topic or article, which results in an enormous …
in the form of opinions and views about any topic or article, which results in an enormous …
Progress, achievements, and challenges in multimodal sentiment analysis using deep learning: A survey
A Pandey, DK Vishwakarma - Applied Soft Computing, 2024 - Elsevier
Sentiment analysis is a computational technique that analyses the subjective information
conveyed within a given expression. This encompasses appraisals, opinions, attitudes or …
conveyed within a given expression. This encompasses appraisals, opinions, attitudes or …
TETFN: A text enhanced transformer fusion network for multimodal sentiment analysis
Multimodal sentiment analysis (MSA), which aims to recognize sentiment expressed by
speakers in videos utilizing textual, visual and acoustic cues, has attracted extensive …
speakers in videos utilizing textual, visual and acoustic cues, has attracted extensive …
A novel machine learning approach for sentiment analysis on Twitter incorporating the universal language model fine-tuning and SVM
B AlBadani, R Shi, J Dong - Applied System Innovation, 2022 - mdpi.com
Twitter sentiment detectors (TSDs) provide a better solution to evaluate the quality of service
and product than other traditional technologies. The classification accuracy and detection …
and product than other traditional technologies. The classification accuracy and detection …
Topic-level sentiment analysis of social media data using deep learning
Due to the inception of Web 2.0 and freedom to facilitate the dissemination of information,
sharing views, expressing opinions with regards to current world level events, services …
sharing views, expressing opinions with regards to current world level events, services …
CTFN: Hierarchical learning for multimodal sentiment analysis using coupled-translation fusion network
Multimodal sentiment analysis is the challenging research area that attends to the fusion of
multiple heterogeneous modalities. The main challenge is the occurrence of some missing …
multiple heterogeneous modalities. The main challenge is the occurrence of some missing …
Urdu sentiment analysis via multimodal data mining based on deep learning algorithms
Every day, a massive amount of text, audio, and video data is published on websites all over
the world. This valuable data can be used to gauge global trends and public perceptions …
the world. This valuable data can be used to gauge global trends and public perceptions …
BAFN: Bi-direction attention based fusion network for multimodal sentiment analysis
Attention-based networks currently identify their effectiveness in multimodal sentiment
analysis. However, existing methods ignore the redundancy of auxiliary modalities. More …
analysis. However, existing methods ignore the redundancy of auxiliary modalities. More …
Memristor-based hierarchical attention network for multimodal affective computing in mental health monitoring
We present a circuit design of the hierarchical attention network for multimodal affective
computing, which can be used in mental health monitoring. Specifically, a kind of cost …
computing, which can be used in mental health monitoring. Specifically, a kind of cost …
A comparative study on bio-inspired algorithms for sentiment analysis
A Yadav, DK Vishwakarma - Cluster Computing, 2020 - Springer
Data mining is one of the most explored and ongoing areas of research. Sentiment analysis
is a popular application of data mining, where the information regarding the customer's …
is a popular application of data mining, where the information regarding the customer's …