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2021 | OriginalPaper | Chapter

Sentiment Analysis of English-Punjabi Code-Mixed Social Media Content to Predict Elections

Authors : Mukhtiar Singh, Vishal Goyal, Sahil Raj

Published in: Advances in Information Communication Technology and Computing

Publisher: Springer Singapore

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Abstract

On social media, the number of users are increasing exponentially. The information contents posted and tweeted by the user are also increasing exponentially. A different meaning of the sentiment is hidden inside the message. Analysing the nature of the text is still a very challenging task. The sentiment analysis is one of the emerging and challenging fields. In the proposed work, the data has been extracted from Twitter with the dataset of around 145,464 comments. In particular, the English-Punjabi dictionary has been created for opinionated word. The opinionated words are categorized into two parts as positive dictionary and negative dictionary. These are stored in gazetteer list and then a statistical technique has been applied for sentiment analysis.

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previous chapter Software Effort Estimation Using Machine Learning Techniques
next chapter Automatic Understanding of Code Mixed Social Media Text: A State of the Art
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Metadata
Title
Sentiment Analysis of English-Punjabi Code-Mixed Social Media Content to Predict Elections
Authors
Mukhtiar Singh
Vishal Goyal
Sahil Raj
Copyright Year
2021
Publisher
Springer Singapore
Book
Advances in Information Communication Technology and Computing

Print ISBN: 978-981-15-5420-9

Electronic ISBN: 978-981-15-5421-6

Copyright Year: 2021

DOI
https://doi.org/10.1007/978-981-15-5421-6_9