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ISSN: 2321-9939 | ESTD Year: 2013

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Paper Title
Recommendation System Through Sentiment Analysis Of Twitter Data
  Samika Rastogi,  G.R. Smitha

Twitter is widely used by several people for networking. It is a platform where people openly express their opinions on any and every subject. The data can be further extracted from twitter to draw meaningful insights on a specific subject. This data, drawn from twitter can be consider a legitimate feedback from the customers or user, regarding a specific product. Customer product reviews play a vital part in the customer’s judgement to purchase a product or use a facility. In this paper a recommender system which is constructed on sentiment analysis on online tweets is proposed. The purpose of this system is to create the most accurate recommendation system by also performing sentiment analysis on tweets procured, using relevant keywords described in a config file .The models are also able to make the predictions within an order of a 30 milliseconds which was a very crucial specification for the onboard embedded systems to operate. The models are also able to achieve a considerable level of accuracy of about 90%, which was required for its proper functioning.

Keywords- Recommendation System, Sentiment Analysis, Twitter Data
Publication Details
Unique Identification Number - IJEDR1904054
Page Number(s) - 303-307
Pubished in - Volume 7 | Issue 4 | October 2019
DOI (Digital Object Identifier) -   
Publisher - IJEDR (ISSN - 2321-9939)
Cite this Article
  Samika Rastogi,  G.R. Smitha,   "Recommendation System Through Sentiment Analysis Of Twitter Data", International Journal of Engineering Development and Research (IJEDR), ISSN:2321-9939, Volume.7, Issue 4, pp.303-307, October 2019, Available at :http://www.ijedr.org/papers/IJEDR1904054.pdf
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