International Journal of Computer Science & Engineering Technology

ISSN : 2229-3345

Open Access
Open Access

ABSTRACT

Title : Survey on Sentiment Analysis for Twitter
Authors : Ankita Gupta, Jyotika Pruthi
Keywords : Sentiment analysis, web 2.0, supervised learning, machine learning, semantic, opinionated
Issue Date : Mar 2017
Abstract :
Social media has revolutionized the communication among the people. Extracted sentiments are very valuable for decision making. Sentiment analysis is an approach of determining people attitude towards any topic. Main goal is to classify a piece of opinionated text containing expressed opinions into positive, negative or neutral and also determine strength of polarity (strongly positive, mildly negative etc.). This paper presents a review on various tools and techniques that has been used by various researchers in existing literature for sentiment analysis of tweets. Thus aim is to provide illustration of research trend in sentiment analysis.
Page(s) : 51-60
ISSN : 2229-3345
Source : Vol. 8, Issue.03

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