Measuring praise and criticism: Inference of semantic orientation from association
ACM Transactions on Information Systems (TOIS)
Predicting the semantic orientation of adjectives
ACL '98 Proceedings of the 35th Annual Meeting of the Association for Computational Linguistics and Eighth Conference of the European Chapter of the Association for Computational Linguistics
Effects of adjective orientation and gradability on sentence subjectivity
COLING '00 Proceedings of the 18th conference on Computational linguistics - Volume 1
Thumbs up or thumbs down?: semantic orientation applied to unsupervised classification of reviews
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
Using appraisal groups for sentiment analysis
Proceedings of the 14th ACM international conference on Information and knowledge management
Learning subjective nouns using extraction pattern bootstrapping
CONLL '03 Proceedings of the seventh conference on Natural language learning at HLT-NAACL 2003 - Volume 4
Learning extraction patterns for subjective expressions
EMNLP '03 Proceedings of the 2003 conference on Empirical methods in natural language processing
Recognizing contextual polarity in phrase-level sentiment analysis
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
Opinion Mining and Sentiment Analysis
Foundations and Trends in Information Retrieval
The good, the bad, and the unknown: morphosyllabic sentiment tagging of unseen words
HLT-Short '08 Proceedings of the 46th Annual Meeting of the Association for Computational Linguistics on Human Language Technologies: Short Papers
Analysis and development of Urdu POS tagged corpus
ALR7 Proceedings of the 7th Workshop on Asian Language Resources
A survey on the role of negation in sentiment analysis
NeSp-NLP '10 Proceedings of the Workshop on Negation and Speculation in Natural Language Processing
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics
Lexicon based sentiment analysis of Urdu text using SentiUnits
MICAI'10 Proceedings of the 9th Mexican international conference on Advances in artificial intelligence: Part I
Unsupervised extraction of appraisal expressions
AI'10 Proceedings of the 23rd Canadian conference on Advances in Artificial Intelligence
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The paper investigates and proposes the treatment of the effect of the phrase-level negation on the sentiment analysis of the Urdu text based reviews. The negation acts as the valence shifter and flips or switches the inherent sentiments of the subjective terms in the opinionated sentences. The presented approach focuses on the subjective phrases called the SentiUnits, which are made by the subjective terms (adjectives), their modifiers, conjunctions, and the negation. The final effect of these phrases is computed according to the given model. The analyzer takes one sentence from the given review, extracts the constituent SentiUnits, computes their overall effect (polarity) and then calculates the final sentence polarity. Using this approach, the effect of negation is handled within these subjective phrases. The main contribution of the research is to deal with a morphologically rich, and resource poor language, and despite of being a pioneering effort in handling negation for the sentiment analysis of the Urdu text, the results of experimentation are quit encouraging.