Abstract
Ever Since its birth in the late 60’s, Internet has been widely and mainly used for interaction purpose only; but over the period of time, its application has changed significantly. Now a days’ Internet is no longer use only for communication purpose. Its use is spread over wide variety of applications’ and E-Commerce is one of them. The most important part in e-commerce, from consumer perspective is, the reviews associated with products. Most of the people do their decision making, based on these online reviews about products or services. These reviews not only help user to know the product or service thoroughly but also affect user’s decision making ability to a great extent and also divert the sentiments about the product positively or negatively. As a result, there have been attempts made, to change the product sentiments positively or negatively by manipulating the online reviews artificially to gain the business benefits. Ultimately, affect the genuine business experience of the user. Therefore in this paper, we have dealt with this particular problem of e-commerce field, specifically online reviews’ in particular and sentiment analysis domain as a whole, in general. A ton of work has been already done in this domain since last decade. In this paper, we will see cumulative study of all this work and how one should approach to deep dive into sentiment analysis field and start research from the scratch. This paper will provide insight of sentiment analysis domain, its general workflow and systematic approach towards solving problems in this domain.
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Jadhav, H.B., Jadhav, A.B. (2020). Systematic Approach Towards Sentiment Analysis in Online Review’s. In: Pandian, A.P., Senjyu, T., Islam, S.M.S., Wang, H. (eds) Proceeding of the International Conference on Computer Networks, Big Data and IoT (ICCBI - 2018). ICCBI 2018. Lecture Notes on Data Engineering and Communications Technologies, vol 31. Springer, Cham. https://doi.org/10.1007/978-3-030-24643-3_43
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DOI: https://doi.org/10.1007/978-3-030-24643-3_43
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