Abstract This study is based on a benchmark corpora consisting of 3,015 textual Arabic opinions collected from Facebook. These collected Arabic opinions are distributed equally among three domains (Food, Sport, and Weather), to create a balanced benchmark corpus. To accomplish this study ten Arabic lexicons were constructed manually, and a new tool called Arabic Opinions Polarity Identification (AOPI) is designed and implemented to identify the polarity of the collected Arabic opinions using the constructed lexicons. Furthermore, this study includes a comparison between the constructed tool and two free online sentiment analysis tools (SocialMention and SentiStrength) that support the Arabic language. The effect of stemming on the accuracy of these tools is tested in this study. The evaluation results using machine learning classifiers show that AOPI is more effective than the other two free online sentiment analysis tools using a stemmed dataset.

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[37] Witten I. And Frank E., Data Mining: Practical Machine Learning Tools and Techniques, Morgan Kaufmann Series in Data Management Systems, 2005. Mohammed Al-Kabi obtained his PhD degree in Mathematics from the University of Lodz/Poland 2001, his master s degree in Computer Science from the University of Baghdad/Iraq 1989, and his bachelor degree in statistics from the University of Baghdad/Iraq 1981. He is an assistant Professor in the Computer Science Department, Faculty of IT, at Zarqa University. He is the author of more than 88 peer-reviewed articles in IR, Big Data, Sentiment Analysis, NLP, Data mining and software Engineering. His teaching interests focus on Information retrieval, big data, web programming, data mining, DBMS (ORACLE and MS Access). Izzat Alsmadi is an associate professor in the Department Of Computer Science at University of New Haven. He obtained his PhD degree in software engineering from NDSU (USA), his second master in software engineering from NDSU (USA) and his first master in CIS from University of Phoenix (USA). He has several published books, Journals and Conference articles largely in software engineering, data mining, IR and NLP. Rawan Khasawneh is a full time lecturer in the department of Computer Information Systems at Jordan University of Science and Technology. She obtained her master degree in Management Information Systems from Yarmouk University in Jordan (2013), and her bachelor degree in Management Information Systems from Yarmouk University in Jordan (2011). Khasawneh s research interests include: e-government, social media and sentiment analysis, E-marketing and E-CRM, knowledge management systems and group decision support systems. Heider Wahsheh obtained his Master degree in Computer Information Systems from Yarmouk University, Jordan, 2012. Between 2013-2015 he worked as a lecturer in the college of Computer Science at King Khalid University, Saudi Arabia. His research interests include information retrieval, sentiment analysis, NLP, data mining, and mobile agent systems