Example of sentiment analysis: Sentiment analysis is performed on Twitter to know the opinion on a particular trending topic, such as many researches have done research and Twitter sentiment analysis during COVI
This book gathers selected papers presented at International Conference on Sentimental Analysis and Deep Learning (ICSADL 2022), jointly organized by Tribhuvan University, Nepal and Prince of Songkla University, Thailand during 16 鈥 17 June, 2022. The volume discusses state-of-the-art research ...
Aspect-based sentiment analysis: an overview in the use of arabic language Artif. Intell. Rev. (2022), pp. 1-39 Google Scholar [55] S.O. Alhumoud, A.A. Al Wazrah Arabic sentiment analysis using recurrent neural networks: a review Artif. Intell. Rev., 55 (1) (2022), pp. 707-...
With extensive research happening on both neural network and non-neural network-based models, the accuracy of sentiment analysis and classification tasks is destined to improve. Earlier, a major challenge associated with Deep Learning models was that the neural network architectures were highly speciali...
SALLD-2 @ LREC 2022 – 2nd Workshop on Sentiment Analysis & Linguistic Linked Data – Call for Papers The SALLD-2 half-day workshop will be held in conjunction with LREC 2022 in Marseille, France, on June 24, 2022. It will provide a discussion forum about usage of Linguistic Linked Da...
(2022). Multimodal sentiment analysis: A survey and comparison. Research anthology on implementing sentiment analysis across multiple disciplines (pp. 1846–1870). https://doi.org/10.4018/IJSSMET.2019040103 Lai, S., Hu, X., Xu, H., et al. (2023). Multimodal sentiment analysis: A survey. ...
Multimodal sentiment analysis (MSA) aims to use a variety of sensors to obtain and process information to predict the intensity and polarity of human emotions. The main challenges faced by current multi-modal sentiment analysis include: how the model ext
Gupta and colleagues [18] examine research papers on sentiment analysis on Twitter, summarizing the methodologies, and models, and presenting a generalized approach implemented in Python. Hasan et al. [19], examined hashtags as emotion labels through two user studies—psychology experts and the gener...
Sentiment analysis has been a well-studied research direction in computational linguistics. Deep neural network models, including convolutional neural networks (CNN) and recurrent neural networks (RNN), yield promising results on text classification tasks. RNN-based architectures, such as, long short-ter...
Some subcategories of research in sentiment analysis include: multimodal sentiment analysis, aspect-based sentiment analysis, fine-grained opinion analysis, language specific sentiment analysis. More recently, deep learning techniques, such as RoBERTa and T5, are used to train high-performing sentiment ...