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2015 | OriginalPaper | Chapter

Sentiment Classification: An Approach for Indian Language Tweets Using Decision Tree

Authors : Sudha Shanker Prasad, Jitendra Kumar, Dinesh Kumar Prabhakar, Sukomal Pal

Published in: Mining Intelligence and Knowledge Exploration

Publisher: Springer International Publishing

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Abstract

This paper describes the system we used for Shared Task on Sentiment Analysis in Indian Languages (SAIL) Tweets, at MIKE-2015. Twitter is one of the most popular platform which allows users to share their opinion in the form of tweets. Since it restricts the users with 140 characters, the tweets are actually very short to carry opinions and sentiments to analyze. We take the help of a twitter training dataset in Indian Language (Hindi) and apply data mining approaches for analyzing the sentiments. We used a state-of-the-art Data Mining tool Weka to automatically classify the sentiment of Hindi tweets into positive, negative or neutral.

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previous chapter Shared Task on Sentiment Analysis in Indian Languages (SAIL) Tweets - An Overview
next chapter Sentiment Classification for Hindi Tweets in a Constrained Environment Augmented Using Tweet Specific Features
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Metadata
Title
Sentiment Classification: An Approach for Indian Language Tweets Using Decision Tree
Authors
Sudha Shanker Prasad
Jitendra Kumar
Dinesh Kumar Prabhakar
Sukomal Pal
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_62

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