Multimodal textTwitterSentimentContext-awareOptical character recognitionText-driven sentiment analysis has been widely studied in the past decade, on both random and benchmark textual Twitter datasets. Few pertinent studies have also reported visual analysis of images to predict sentiment, but much of ...
In recent years, multimodal natural language processing, aimed at learning from diverse data types, has garnered significant attention. However, there needs to be more clarity when it comes to analysing multimodal tasks in multi-lingual contexts. While prior studies on sentiment analysis of tweets ...
Therefore, how to automatically detect the sentiment of the multimodal data has been increasingly attracting attention in both academia and industry. However, it is still a challenging task to deal with the multimodal data for sentiment analysis. First, in contrast to traditional single modality ...
Twitter sentiment analysis: The good the bad and the omg!. Icwsm, 11, 538-541.Varsha Sahayak, Vijaya Shete, Apashabi Pathan, "Sentiment Analysis on Twitter Data", International Journal of Innovative Research in Advanced... V Sahayak,V Shete,A Pathan 被引量: 27发表: 2015年 Proceedings of ...
Premananda Jana, in Advanced Data Mining Tools and Methods for Social Computing, 2022 Abstract With the rise of technology, anyone can easily share their sentiments through social media platforms like Facebook, Twitter, LinkedIn, Google+, and Instagram. Sentiment analysis is a technique that ...
With the rise of image sharing mode on social media platforms, text cannot fully reveal users’ emotions, so people begin to study multimodal sentiment analysis by combining text and images. Previous researches on sarcasm detection have used Bidirectional Long Short-term Memory Network (Bi-LSTM) ...
10. Relation-Aware Collaborative Learning for Unified Aspect-Based Sentiment Analysis会议:ACL 2020.作者:Zhuang Chen, Tieyun Qian链接:aclweb.org/anthology/2011. CH-SIMS: A Chinese Multimodal Sentiment Analysis Dataset with Fine-grained Annotation of Modality会议:ACL 2020.作者:Wenmeng Yu, Hua Xu, ...
Sentiment Analysis techniques can be categorized into machine learning approaches, lexicon-based approaches, and even hybrid methods. Some subcategories of research in sentiment analysis include: multimodal sentiment analysis, aspect-based sentiment analysis, fine-grained opinion analysis, language specific sen...
Nevertheless, multimodal sentiment analysis remains a highly challenging task. Firstly, since the emotional information in different modal data is diverse, it is necessary to effectively extract and represent the emotional features of these modalities during sentiment analysis. From the perspective of ...
Sentiment analysis from text is currently widely used for customer satisfaction assessment and brand perception analysis, among others. With the proliferation of social media, multimodal sentiment analysis is set to bring new opportunities with the arrival of complementary data streams for improving and ...