Sentiment analysis in arabic: opinion polarity detection
作者： Mohammed Rushdi Saleh
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摘要: espanolEl analisis de sentimientos esta obteniendo una gran importancia debido al aumento popularidad la web 2.0. Esta memoria se centra en el estudio diferentes aspectos del sentimientos. El primer objetivo es analizar las opiniones que provienen arabe y predecir su polaridad. Para alcanzar este han generado dos corpora: OCA EVOCA. un corpus opinion peliculas arabe, EVOCA paralelo a incluye traduccion ingles opiniones. Otro consiste adaptado dominios. ello, ha SINAI-SA aplicado distintas tecnicas aprendizaje automatico. Finalmente, realiza sobre revisiones neutrales. llevar cabo objetivo, investigado enfoque principales, uno basado orientacion semantica otro algoritmos automatico como SVM o NB. EnglishSentiment analysis is becoming increasingly important due the growing popularity of Web This study focuses mainly on how to analyze opinions in Arabic language and predict their polarity. To achieve that, two corpora have been generated (OCA EVOCA), an for movie reviews, while translated version English. Another was created (SINAI-SA corpus) used with other order sentiments different domains. SINAI also sort comments behave as textual information prediction customer rates. question that solved this “How treat neutral reviews”. Two main approaches investigated research, one based semantic orientation machine learning algorithms like or NB
unirioja.es参考文章(64)
Kimberly D. Voll, Maite Taboada, Caroline Anthony, Methods for Creating Semantic Orientation Dictionaries. language resources and evaluation. pp. 427- 432 ,(2006)
Leah S. Larkey, Lisa Ballesteros, Margaret E. Connell, Light Stemming for Arabic Information Retrieval Springer, Dordrecht. pp. 221- 243 ,(2007) , 10.1007/978-1-4020-6046-5_12
Andrea Esuli, Fabrizio Sebastiani, SENTIWORDNET: A Publicly Available Lexical Resource for Opinion Mining language resources and evaluation. pp. 417- 422 ,(2006)
Eugenio Martínez-Cámara, M. Teresa Martín-Valdivia, L. Alfonso Ureña-López, Opinion classification techniques applied to a Spanish corpus international conference natural language processing. pp. 169- 176 ,(2011) , 10.1007/978-3-642-22327-3_17
Khurshid Ahmad, David Cheng, Yousif Almas, Multi-lingual Sentiment Analysis of Financial News Streams Proceedings of 1st International Workshop on Grid Technology for Financial Modeling and Simulation — PoS(GRID2006). ,(2007) , 10.22323/1.026.0001
Nigel Collier, Tony Mullen, Sentiment Analysis using Support Vector Machines with Diverse Information Sources empirical methods in natural language processing. pp. 412- 418 ,(2004)
J. Wiebe, Identifying Collocations for Recognizing Opinions meeting of the association for computational linguistics. ,(2001)
Jack Grieve, Maite Taboada, Analyzing Appraisal Automatically pp. 158- 161 ,(2004)
Nikola Ljubesic, Zeljko Agic, Marko Tadic, Towards Sentiment Analysis of Financial Texts in Croatian language resources and evaluation. ,(2010)
Janyce Wiebe, Learning Subjective Adjectives from Corpora national conference on artificial intelligence. pp. 735- 740 ,(2000)