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
Opinion Mining and Sentiment Analysis
Foundations and Trends in Information Retrieval
Adapting Naive Bayes to Domain Adaptation for Sentiment Analysis
ECIR '09 Proceedings of the 31th European Conference on IR Research on Advances in Information Retrieval
Sentiment analysis of blogs by combining lexical knowledge with text classification
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
Assas-Band, an affix-exception-list based Urdu stemmer
ALR7 Proceedings of the 7th Workshop on Asian Language Resources
A comparison of sentiment analysis techniques: polarizing movie blogs
Canadian AI'08 Proceedings of the Canadian Society for computational studies of intelligence, 21st conference on Advances in artificial intelligence
Multiple source adaptation and the Rényi divergence
UAI '09 Proceedings of the Twenty-Fifth Conference on Uncertainty in Artificial Intelligence
HLT '10 Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics
Unsupervised extraction of appraisal expressions
AI'10 Proceedings of the 23rd Canadian conference on Advances in Artificial Intelligence
Challenges in Urdu stemming: a progress report
FDIA'07 Proceedings of the 1st BCS IRSG conference on Future Directions in Information Access
Sentiment analysis of urdu language: handling phrase-level negation
MICAI'11 Proceedings of the 10th Mexican international conference on Advances in Artificial Intelligence - Volume Part I
Associating targets with SentiUnits: a step forward in sentiment analysis of Urdu text
Artificial Intelligence Review
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Like other languages, Urdu websites are becoming more popular, because the people prefer to share opinions and express sentiments in their own language. Sentiment analyzers developed for other well-studied languages, like English, are not workable for Urdu, due to their scriptic, morphological, and grammatical differences. As a result, this language should be studied as an independent problem domain. Our approach towards sentiment analysis is based on the identification and extraction of SentiUnits from the given text, using shallow parsing. SentiUnits are the expressions, which contain the sentiment information in a sentence. We use sentiment-annotated lexicon based approach. Unluckily, for Urdu language no such lexicon exists. So, a major part of this research consists in developing such a lexicon. Hence, this paper is presented as a base line for this colossal and complex task. Our goal is to highlight the linguistic (grammar and morphology) as well as technical aspects of this multidimensional research problem. The performance of the system is evaluated on multiple texts and the achieved results are quite satisfactory.