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Chao He, Xinghua Zhang, Dongqing Song, Yingshan Shen, Chengjie Mao, Huosheng Wen, Dingju Zhu and Lihua Cai
With the popularization of better network access and the penetration of personal smartphones in today?s world, the explosion of multi-modal data, particularly opinionated video messages, has created urgent demands and immense opportunities for Multi-Moda...
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Xingxing Tong, Ming Chen and Guofu Feng
The issue of aquatic product quality and safety has gradually become a focal point of societal concern. Analyzing textual comments from people about aquatic products aids in promptly understanding the current sentiment landscape regarding the quality and...
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Haidi Badr, Nayer Wanas and Magda Fayek
Unsupervised domain adaptation (UDA) presents a significant challenge in sentiment analysis, especially when faced with differences between source and target domains. This study introduces Weighted Sequential Unsupervised Domain Adaptation (WS-UDA), a no...
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Mahammad Khalid Shaik Vadla, Mahima Agumbe Suresh and Vimal K. Viswanathan
Understanding customer emotions and preferences is paramount for success in the dynamic product design landscape. This paper presents a study to develop a prediction pipeline to detect the aspect and perform sentiment analysis on review data. The pre-tra...
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Peranut Nimitsurachat and Peter Washington
Emotion recognition models using audio input data can enable the development of interactive systems with applications in mental healthcare, marketing, gaming, and social media analysis. While the field of affective computing using audio data is rich, a m...
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Yao Qin, Yiping Shi, Xinze Hao and Jin Liu
Microblog is an important platform for mining public opinion, and it is of great value to conduct emotional analysis of microblog texts during the current epidemic. Aiming at the problem that most current emotional classification methods cannot effective...
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Dongling Ma, Chunhong Zhang, Liang Zhao, Qingji Huang and Baoze Liu
Monitoring, analyzing, and managing public sentiment surrounding urban emergencies hold significant importance for city governments in executing effective response strategies and maintaining social stability. In this study, we present a study which was c...
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Shelley Gupta, Archana Singh and Vivek Kumar
Virtual users generate a gigantic volume of unbalanced sentiments over various online crowd-sourcing platforms which consist of text, emojis, or a combination of both. Its accurate analysis brings profits to various industries and their services. The sta...
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Shi Li and Xiaoting Chen
The task of joint dialogue act recognition (DAR) and sentiment classification (DSC) aims to predict both the act and sentiment labels of each utterance in a dialogue. Existing methods mainly focus on local or global semantic features of the dialogue from...
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Rui Zhang, Chengrong Xue, Qingfu Qi, Liyuan Lin, Jing Zhang and Lun Zhang
The enrichment of social media expression makes multimodal sentiment analysis a research hotspot. However, modality heterogeneity brings great difficulties to effective cross-modal fusion, especially the modality alignment problem and the uncontrolled ve...
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