Effective lexicon-based approach for Urdu sentiment analysis
| Autor: | Mohammad Abid Khan, Neelam Mukhtar |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
Linguistics and Language
Recall Computer science business.industry Sentiment analysis 02 engineering and technology Lexicon computer.software_genre Language and Linguistics language.human_language Cohen's kappa Negation Artificial Intelligence 020204 information systems Noun 0202 electrical engineering electronic engineering information engineering language 020201 artificial intelligence & image processing Urdu Artificial intelligence business computer Natural language processing |
| Zdroj: | Artificial Intelligence Review. 53:2521-2548 |
| ISSN: | 1573-7462 0269-2821 |
| DOI: | 10.1007/s10462-019-09740-5 |
| Popis: | The lexicon-based approach is used for sentiment analysis of Urdu. In the lexicon, apart from the traditional approach of having adjectives, nouns and negations we have also included verbs, intensifiers and context-dependent words. An effective Urdu sentiment analyzer is developed that applies rules and make use of this new lexicon and perform Urdu sentiment analysis by classifying sentences as positive, negative or neutral. Evaluating this Urdu sentiment analyzer, by using sentences from Urdu blogs, yields the most promising results so far in Urdu language with 89.03% accuracy with 0.86 precision, 0.90 recall and 0.88 F-measure. Results are evaluated using kappa statistics as well. The comparison with the previous work in Urdu shows that the combination of this Urdu sentiment lexicon and Urdu sentiment analyzer is much more effective than the previous such combinations. The main reason for increased efficiency is the development of wide coverage lexicon and effective handling of negations, intensifiers and context-dependent words by the Urdu sentiment analyzer. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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