Arabic opinion target extraction from tweets
Twitter is an ocean of sentiments; users can express their opinion freely on a wide variety of topics. The unique characteristics that twitter holds introduce a different level of challenge in the field of sentiment analysis. Identifying the topic or the target of the expressed opinion is the aim of...
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Asian Research Publishing Network
2015
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my.utm.578882021-09-26T15:46:17Z http://eprints.utm.my/id/eprint/57888/ Arabic opinion target extraction from tweets Alhazmi, Marwa Salim, Naomie QA75 Electronic computers. Computer science Twitter is an ocean of sentiments; users can express their opinion freely on a wide variety of topics. The unique characteristics that twitter holds introduce a different level of challenge in the field of sentiment analysis. Identifying the topic or the target of the expressed opinion is the aim of this study; Opinion target recognition is a task that has not been considered yet in Arabic Language. In this paper we propose a method to extract the opinion target from tweets written in Arabic language. The task is carried out in three phases. Phase 1: preprocess the tweet to delete unnecessary entities like mentions and URLs. Phase 2: construct a feature set from tweet words to be used in the classifying phase; these features are part-of-speech, Named entities, English words, tweet hash tags and part-of-speech pattern. Phase 3: Three classifiers are trained using the extracted features, to assign each word in the tweet to be either an opinion target or not, these classifiers are: Naïve Bayes, Support vector machine and k-nearest neighbor, with an F-Measure result reaching 91%. 500 tweets are used for the experiment, where the opinion target was manually tagged. Finally, a comparison between the results of each model is conducted. Asian Research Publishing Network 2015 Article PeerReviewed Alhazmi, Marwa and Salim, Naomie (2015) Arabic opinion target extraction from tweets. ARPN Journal of Engineering and Applied Sciences, 10 (3). pp. 1023-1026. ISSN 1819-6608 http://www.arpnjournals.com/jeas/volume_03_2015.htm |
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QA75 Electronic computers. Computer science Alhazmi, Marwa Salim, Naomie Arabic opinion target extraction from tweets |
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Twitter is an ocean of sentiments; users can express their opinion freely on a wide variety of topics. The unique characteristics that twitter holds introduce a different level of challenge in the field of sentiment analysis. Identifying the topic or the target of the expressed opinion is the aim of this study; Opinion target recognition is a task that has not been considered yet in Arabic Language. In this paper we propose a method to extract the opinion target from tweets written in Arabic language. The task is carried out in three phases. Phase 1: preprocess the tweet to delete unnecessary entities like mentions and URLs. Phase 2: construct a feature set from tweet words to be used in the classifying phase; these features are part-of-speech, Named entities, English words, tweet hash tags and part-of-speech pattern. Phase 3: Three classifiers are trained using the extracted features, to assign each word in the tweet to be either an opinion target or not, these classifiers are: Naïve Bayes, Support vector machine and k-nearest neighbor, with an F-Measure result reaching 91%. 500 tweets are used for the experiment, where the opinion target was manually tagged. Finally, a comparison between the results of each model is conducted. |
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Article |
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Alhazmi, Marwa Salim, Naomie |
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Alhazmi, Marwa Salim, Naomie |
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Alhazmi, Marwa |
title |
Arabic opinion target extraction from tweets |
title_short |
Arabic opinion target extraction from tweets |
title_full |
Arabic opinion target extraction from tweets |
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Arabic opinion target extraction from tweets |
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Arabic opinion target extraction from tweets |
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arabic opinion target extraction from tweets |
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Asian Research Publishing Network |
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2015 |
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http://eprints.utm.my/id/eprint/57888/ http://www.arpnjournals.com/jeas/volume_03_2015.htm |
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13.18916 |