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With the growth of content on social media networks, enterprises and servicesproviders have become interested in identifying the questions of theircustomers. Tracking these questions become very challenging with the growth oftext that grows directly proportional to the increase of Arabic users thusmaking it very difficult to be tracked manually. By automatic identifying thequestions seeking answers on the social media networks and defining theircategory, we can automatically answer them by finding an existing answer oreven routing them to those responsible for answering those questions in thecustomer service. This will result in saving the time and the effort andenhancing the customer feedback and improving the business. In this paper, wehave implemented a binary classifier to classify Arabic text to either questionseeking answer or not. We have added emotional based features to the state ofthe art features. Experimental evaluation has done and showed that theseemotional features have improved the accuracy of the classifier.

Question Identification in Arabic Language Using Emotional Based Features