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2015 | OriginalPaper | Chapter

AMRITA-CEN@SAIL2015: Sentiment Analysis in Indian Languages

Authors : Shriya Se, R. Vinayakumar, M. Anand Kumar, K. P. Soman

Published in: Mining Intelligence and Knowledge Exploration

Publisher: Springer International Publishing

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Abstract

The contemporary work is done as slice of the shared task in Sentiment Analysis in Indian Languages (SAIL 2015), constrained variety. Social media allows people to create and share or exchange opinions based on many perspectives such as product reviews, movie reviews and also share their thoughts through personal blogs and many more platforms. The data available in the internet is huge and is also increasing exponentially. Due to social media, the momentousness of categorizing these data has also increased and it is very difficult to categorize such huge data manually. Hence, an improvised machine learning algorithm is necessary for wrenching out the information. This paper deals with finding the sentiment of the tweets for Indian languages. These sentiments are classified using various features which are extracted using words and binary features, etc. In this paper, a supervised algorithm is used for classifying the tweets into positive, negative and neutral labels using Naive Bayes classifier.

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previous chapter A Sentiment Analysis System for Indian Language Tweets
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Metadata
Title
AMRITA-CEN@SAIL2015: Sentiment Analysis in Indian Languages
Authors
Shriya Se
R. Vinayakumar
M. Anand Kumar
K. P. Soman
Copyright Year
2015
Book
Mining Intelligence and Knowledge Exploration

Print ISBN: 978-3-319-26831-6

Electronic ISBN: 978-3-319-26832-3

Copyright Year: 2015

DOI
https://doi.org/10.1007/978-3-319-26832-3_67

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