Using Lexicon-Based Opinion Mining to Gauge Customer Satisfaction
Abdelaziz Saleh Mohammad1, Mohammad Al Kadri2

1Abdelaziz Saleh Mohammad*, Department of Computer Science, Jamia Millia Islamia, New Delhi, India.
2Mohammad Al Kadri, Department of Management, Başakşehir Islam Akadamisi Başakşehir, İstanbul, Turkey.
Manuscript received on January 17, 2020. | Revised Manuscript received on January 22, 2020. | Manuscript published on February 10, 2020. | PP: 1817-1824 | Volume-9 Issue-4, February 2020. | Retrieval Number: D1776029420/2020©BEIESP | DOI: 10.35940/ijitee.D1776.029420
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Abstract: The web offers businesses a great tool to get instant feedback from their customers. Decision-makers need to improve the decision quality and increase the business performance, they required applications that provides data analysis and data visualization. In this paper, we will try to test users’ reviews about hotels in Europe, they stayed and left a comment expressing their feelings about their experience, by applying opinion mining and sentimental analysis methodology on 515,000 customers reviews to uncover how effective and useful a lexicon-based Sentiment Analysis system will be for business executives to improve the performance and quality of hotels. We wish to explore key-concepts of sentiment analysis, classification levels, different approaches to Sentiment Analysis. And we will apply step by step SA techniques to preprocess the text, tokenize, lemmatize, analyze text, then produce business intelligence visualization results. 
Keywords: Opinion Mining, Sentiment Analysis, Polarity Analysis, Business Intelligence, Support Decision-Making.
Scope of the Article:  Artificial Intelligence Approaches to Software Engineering