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A Comparative Survey of Multimodal Multilabel Sentiment Analysis and Its Applications Initiated Due to the Impact of COVID-19
5th IEEE International Conference on Advances in Science and Technology, ICAST 2022 ; : 220-224, 2022.
Article in English | Scopus | ID: covidwho-2260500
ABSTRACT
This study presents a detailed survey of different works related to sentiment analysis. The COVID-19 pandemic and its impact on people's mental health act as the driving force behind this survey. The survey can help study sentiment analysis and approaches taken in many studies to detect human emotions via advanced technology. It can also help in improving present systems by finding loopholes and increasing their accuracy. Various lexicon and ML-based systems and models like Word2Vec and LSTM were studied in the surveyed papers. Some of the current and future directions highlighted were Twitter sentiment analysis, review-based market analysis, determining changing behavior and emotions in a given time period, and detecting the mental health of employees, and students. This survey provides details related to trends and topics in sentiment analysis and an in-depth understanding of various technologies used in different studies. It also gives an insight into the wide variety of applications related to sentiment analysis. © 2022 IEEE.
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Full text: Available Collection: Databases of international organizations Database: Scopus Type of study: Experimental Studies / Observational study Language: English Journal: 5th IEEE International Conference on Advances in Science and Technology, ICAST 2022 Year: 2022 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: Scopus Type of study: Experimental Studies / Observational study Language: English Journal: 5th IEEE International Conference on Advances in Science and Technology, ICAST 2022 Year: 2022 Document Type: Article