The evaluation of the public opinion - A case study: MERS-CoV infection virus in KSA

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Abstract

Opinion Mining and Sentiment Analysis are active research trends in natural language processing and data mining. Recently, this research has been extended outside the computer science area to cover other areas such as social science, political science, and business. The explosion of social media such as social networks, Blogs, Twitter, and forums has created unprecedented opportunities for data mining research community. Analyzers can study and analyze users' opinions, attitudes, and emotions about news or social events. Big data focuses on the intelligent analysis of a large amount of data that is typically collected from several different sources. Our focus in this work is to address new challenges raised by combining Apache Hadoop as a big data platform with an opinion mining approach to make a decision we often seek based on collected data from the opinions of people. We presented a case study about MERS virus in KSA to evaluate our proposed approach. A discussion of available dataset and results are also provided.

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Zarrad, A., Jaloud, A., & Alsmadi, I. (2014). The evaluation of the public opinion - A case study: MERS-CoV infection virus in KSA. In Proceedings - 2014 IEEE/ACM 7th International Conference on Utility and Cloud Computing, UCC 2014 (pp. 664–670). Institute of Electrical and Electronics Engineers Inc. https://doi.org/10.1109/UCC.2014.107

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