International Conference on Mining Intelligence and Knowledge Exploration

Mining Intelligence and Knowledge Exploration pp 703-710 | Cite as

AMRITA-CEN@SAIL2015: Sentiment Analysis in Indian Languages

  • Shriya Se
  • R. Vinayakumar
  • M. Anand Kumar
  • K. P. Soman
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9468)

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.

Keywords

Sentiment analysis Features Social media Machine learning Supervised algorithm Naive Bayes classifier 

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Shriya Se
    • 1
  • R. Vinayakumar
    • 1
  • M. Anand Kumar
    • 1
  • K. P. Soman
    • 1
  1. 1.Centre for Excellence in Computational Engineering and NetworkingAmrita Vishwa VidyapeethamCoimbatoreIndia

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