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Sentiment Analysis System for Roman Urdu

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Intelligent Computing (SAI 2018)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 858))

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Abstract

Sentiment analysis is a computational process to identify positive or negative sentiments expressed in a piece of text. In this paper, we present a sentiment analysis system for Roman Urdu. For this task, we gathered Roman Urdu data of 779 reviews for five different domains, i.e., Drama, Movie/Telefilm, Mobile Reviews, Politics, and Miscellaneous (Misc). We selected unigram, bigram and uni-bigram (unigram + bigram) features for this task and used five different classifiers to compute accuracies before and after feature reduction. In total, thirty-six (36) experiments were performed, and they established that Naïve Bayes (NB) and Logistic Regression (LR) performed better than the rest of the classifiers on this task. It was also observed that the overall results were improved after feature reduction.

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Authors and Affiliations

  1. University of New South Wales (UNSW), Kensington, Australia

    Khawar Mehmood, Daryl Essam & Kamran Shafi

Authors
  1. Khawar Mehmood
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  2. Daryl Essam
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  3. Kamran Shafi
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Corresponding author

Correspondence to Khawar Mehmood .

Editor information

Editors and Affiliations

  1. Faculty of Science and Engineering, Department of Information Science, Saga University, Honjo, Saga, Japan

    Kohei Arai

  2. The Science and Information (SAI) Organization, Bradford, West Yorkshire, UK

    Supriya Kapoor

  3. The Science and Information (SAI) Organization, Bradford, West Yorkshire, UK

    Rahul Bhatia

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Mehmood, K., Essam, D., Shafi, K. (2019). Sentiment Analysis System for Roman Urdu. In: Arai, K., Kapoor, S., Bhatia, R. (eds) Intelligent Computing. SAI 2018. Advances in Intelligent Systems and Computing, vol 858. Springer, Cham. https://doi.org/10.1007/978-3-030-01174-1_3

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