Mahmoud Nabil Mahmoud <br/><br/>
Sentiment analysis and keyphrase extraction /  
  اا و ااج ت ا 
Mahmoud Nabil Mahmoud ; Supervised Amir F. Atiya , Mohamed Aly 
 - Cairo :   Mahmoud Nabil Mahmoud ,   2016 
 - 71 P. :   charts , facsimiles ;   30cm. 
<br/><br/>Thesis (M.Sc.) - Cairo University - Faculty of Engineering - Department of Computer Engineering 
<br/><br/> Millions of mutual posts on social media websites every day. This calls for tools to mine social data and extract useful information out of it. Towards this end, this work focuses on four tasks (a)introducing some datasets that can be used for sentiment analysis for Arabic language; (b)performing a sequence of benchmark experiments on each dataset alongside with a method for extracting sentiment lexicons. (c)introducing a deep-learning recurrent neural model for sentiment analysis tested on several SemEval datasets; (d)introducing some new methods for extracting keyphrases from Arabic documents 
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<br/><br/><label>Subjects--Index Terms: </label>Arabic natural language processing Social content analysis Twitter