Abstract
Online archives have received a great deal of attention in recent years from a person’s view and thoughts as primary platform. Set of circumstances gives rise to increasing interest in methods for automatically collecting and evaluating individual opinions from online documents such as customer reviews, Weblogs and comments on electronically accessible media, emphasis of current studies are mainly on attitude analysis. Interest of human beings is on designing a structure which can categorize feelings of individuals in the form of automated letter. Retrieving and determining beliefs from Web require appropriate mechanism that can be used to acquire and estimate thoughts of the desires of online consumers, which could be useful for economic or marketing research. An aspect of natural language processing (NLP), sentiment analysis (SA) has experienced a growing interest in the past decade. The difficulties and chances of this rising field are likewise talked about prompting our postulation that the analysis of multimodal sentiment has a significant untapped potential.
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References
Rani S, Kumar P (2019) A journey of Indian languages over sentiment analysis a systematic review. Artif Intell Rev 52:1415–1462. https://doi.org/10.1007/s10462-018-9670-y
Hussein DME-DM (2018) A survey on sentiment analysis challenges. J King Saud Univ Eng Sci 30(4):330–338. https://doi.org/10.1016/j.jksues.2016.04.002
Iti C, Erik C, Roy W, Francisco H (2017) Distinguishing between facts and opinions for sentiment analysis: survey and challenges, Elsevier
Mäntylä M, Graziotin D, Kuutila M (2018) The evolution of sentiment analysis—a review of research topics venues, and top cited papers, Elsevier
Erik C, Soujanya P, Alexander G, Mike T (2017) Sentiment analysis is a big suitcase. IEEE
Schouten K, Frasincar F (2015) Survey on aspect-level sentiment analysis. IEEE Trans Knowl Data Eng 28(3):813–830
Amandeep K, Vishal G (2013) A survey on sentiment analysis and opinion mining techniques. JETW
Moshe K, Jonathan S (2016) The importance of neutral examples for learning sentiment
Pradhan V, Vala J, Balani P (2016) A survey on sentiment analysis algorithms for opinion mining. Int J Comput Appl
Arti B, Chandak M, Akshay Z (2013) Opinion mining and analysis: a survey. IJNLC
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Shah, P.V., Swaminarayan, P. (2021). Sentiment Analysis—An Evaluation of the Sentiment of the People: A Survey. In: Kotecha, K., Piuri, V., Shah, H., Patel, R. (eds) Data Science and Intelligent Applications. Lecture Notes on Data Engineering and Communications Technologies, vol 52. Springer, Singapore. https://doi.org/10.1007/978-981-15-4474-3_6
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DOI: https://doi.org/10.1007/978-981-15-4474-3_6
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