Towards Sentiment Analysis and Opinion Mining From Multimodal Data
M. Gunasekar1, S.Thilagamani2
1M. Gunasekar, Assistant Professor, Department of Information Technology, M. Kumarasamy College of Engineering Autonomous, Karur (Tamil Nadu), India.
2Dr. S. Thilagamani, Professor Head & Dean, Department of Computer Science and Engineering, M. Kumarasamy College of Engineering Autonomous, Karur (Tamil Nadu), India.
Manuscript received on 21 May 2019 | Revised Manuscript received on 07 June 2019 | Manuscript Published on 15 June 2019 | PP: 272-274 | Volume-8 Issue-1S2 May 2019 | Retrieval Number: A00620581S219/2019©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The ease accessibility of internet and web application paves way for people to express their opinion and emotion to the society. Social networks captures the view of people on products, politics, movie etc., the review given by customers decide the success and leverage the popularity of the product in the market. The challenges rely on the technology, which are employed to trace information accurately from the available data. Sentiment analysis on textual data is widely used to assess the customer satisfaction. Sentiment can also be perceived from the mixture of text, audio, facial expression, visual display etc. This survey defines multimodal sentiment analysis and review recent methods which adopts mixture of inputs for multimodal sentiment analysis. This survey outlines the different approaches followed to extract feature from multimodal data.
Keywords: Cloud Computing, Data Security, User Behavior, Decoy Technology, Fingerprint Authentication, Face Recognition.
Scope of the Article: Data Analytics