Sentiment Analysis for Twitter Data
Deep Kaneria1, Brijesh Patel2

1Deep Kaneria, Department of Computer Engineering, G H Patel College of Engineering & Technology, Vallabh Vidyanagar, Anand (Gujarat), India.

2Brijesh Patel, Assistant Professor, Department of Computer Engineering, GCET, Greater Noida (Uttar Pradesh), India.

Manuscript received on 27 April 2020 | Revised Manuscript received on 09 May 2020 | Manuscript Published on 22 May 2020 | PP: 98-101 | Volume-9 Issue-7S July 2020 | Retrieval Number: 100.1/ijitee.G10190597S20 | DOI: 10.35940/ijitee.G1019.0597S20

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Abstract: With the advancements in web technology and its growth, there’s an incredible volume of information present everywhere on the net for internet users and plenty more data is generated on a daily basis. Internet emerged as place for exchanging ideas, sharing opinions, online learning and political views. Social networking sites such as Facebook, Twitter, are rapidly growing as the users are allowed to post and revel their views on various topics, and can discussion with different groups and communities, or post messages across the world. In the area of sentiment analysis large numbers of researchers are working. The main focus is on twitter data for sentiment analysis, that’s helpful to research the info within the tweets,where opinions are heterogeneous, highly unstructured, and are either positive,or negative, or many cases. In this paper, we provide a study and comparative analysis of existing techniques used for opinion mining through machine learning approach. Naive Bayes & Support Vector Machine, we provide research on twitter data.

Keywords: Machine Learning (ML), Naïve Bayes (NB), Twitter, Support Vector Machine (SVM), Sentiment Analysis (SA).
Scope of the Article: Data Analytic