• DocumentCode
    2626314
  • Title

    Detecting Sentiment in Nepali texts: A bootstrap approach for Sentiment Analysis of texts in the Nepali language

  • Author

    Gupta, Chandan Prasad ; Bal, Bal Krishna

  • Author_Institution
    Dept. of Comput. Sci. & Eng., Kathmandu Univ., Dhulikhel, Nepal
  • fYear
    2015
  • fDate
    3-4 March 2015
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    The increasing amount of Nepali content on the Web has opened doors for the research and development of a number of Natural Language Processing applications including Sentiment Analysis (SA). However, to best of our knowledge there has been no work in this area for Nepali language. In this paper we present two main approaches for sentiment detection of Nepali texts. We have developed Nepali Sentiment Corpus and Nepali SentiWordNet. In our first approach we develop a lexical resource called Bhavanakos, which is a Nepali SentiWordNet and implement a strategy in which sentiment words are detected in Nepali texts to detect the sentiment in documents. The second of our approach we train a machine learning based text classifier with annotated Nepali text data to classify the document.
  • Keywords
    emotion recognition; learning (artificial intelligence); natural language processing; pattern classification; statistical analysis; text analysis; Bhavanakos; Nepali SentiWordNet; Nepali Sentiment Corpus; Nepali content; Nepali language; Nepali text sentiment detection; bootstrap approach; document classification; lexical resource; machine learning based text classifier; natural language processing applications; research and development; text sentiment analysis; Accuracy; Dictionaries; Manuals; Probability; Sentiment analysis; Training; Machine Learning; Nepali Language; Opinion Mining; SentiWordNet; Sentiment Analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Cognitive Computing and Information Processing (CCIP), 2015 International Conference on
  • Conference_Location
    Noida
  • Type

    conf

  • DOI
    10.1109/CCIP.2015.7100739
  • Filename
    7100739