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Tag Me a Label with Multi-arm: Active Learning for Telugu Sentiment Analysis

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Big Data Analytics and Knowledge Discovery (DaWaK 2017)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 10440))

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Abstract

Sentiment Analysis is one of the most active research areas in natural language processing and an extensively studied problem in data mining, web mining and text mining for English language. With the proliferation of social media these days, data is widely increasing in regional languages along with English. Telugu is one such regional language with abundant data available in social media, but it’s hard to find a labeled training set as human annotation is time-consuming and cost-ineffective. To address this issue, in this paper the practicality of active learning for Telugu sentiment analysis is investigated. We built a hybrid approach by combining different query selection strategy frameworks to increase more accurate training data instances with limited labeled data. Using a set of classifiers like SVM, XGBoost, and Gradient Boosted Trees (GBT), we achieved promising results with minimal error rate.

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Notes

  1. 1.

    https://www.ethnologue.com/statistics/size.

  2. 2.

    https://en.wikipedia.org/wiki/Telugu_language.

  3. 3.

    https://en.wikipedia.org/wiki/WX_notation.

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Author information

Authors and Affiliations

  1. LTRC, KCIS, IIIT Hyderabad, Hyderabad, India

    Sandeep Sricharan Mukku & Radhika Mamidi

  2. Teradata, Hyderabad, India

    Subba Reddy Oota

Authors
  1. Sandeep Sricharan Mukku
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  2. Subba Reddy Oota
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  3. Radhika Mamidi
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Corresponding authors

Correspondence to Sandeep Sricharan Mukku or Subba Reddy Oota .

Editor information

Editors and Affiliations

  1. LIAS/ISAE-ENSMA, Chasseneuil, France

    Ladjel Bellatreche

  2. University of Texas at Arlington, Arlington, Texas, USA

    Sharma Chakravarthy

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Mukku, S.S., Oota, S.R., Mamidi, R. (2017). Tag Me a Label with Multi-arm: Active Learning for Telugu Sentiment Analysis. In: Bellatreche, L., Chakravarthy, S. (eds) Big Data Analytics and Knowledge Discovery. DaWaK 2017. Lecture Notes in Computer Science(), vol 10440. Springer, Cham. https://doi.org/10.1007/978-3-319-64283-3_26

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  • DOI: https://doi.org/10.1007/978-3-319-64283-3_26

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  • Online ISBN: 978-3-319-64283-3

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