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Intelligent Strategy and Security in Education: Big Data (Text Analytics)

Intelligent Strategy and Security in Education: Big Data (Text Analytics)

Samson Oluwaseun Fadiya
Copyright: © 2019 |Pages: 24
ISBN13: 9781522589761|ISBN10: 1522589767|ISBN13 Softcover: 9781522589778|EISBN13: 9781522589785
DOI: 10.4018/978-1-5225-8976-1.ch004
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MLA

Fadiya, Samson Oluwaseun. "Intelligent Strategy and Security in Education: Big Data (Text Analytics)." Applying Methods of Scientific Inquiry Into Intelligence, Security, and Counterterrorism, edited by Arif Sari, IGI Global, 2019, pp. 87-110. https://doi.org/10.4018/978-1-5225-8976-1.ch004

APA

Fadiya, S. O. (2019). Intelligent Strategy and Security in Education: Big Data (Text Analytics). In A. Sari (Ed.), Applying Methods of Scientific Inquiry Into Intelligence, Security, and Counterterrorism (pp. 87-110). IGI Global. https://doi.org/10.4018/978-1-5225-8976-1.ch004

Chicago

Fadiya, Samson Oluwaseun. "Intelligent Strategy and Security in Education: Big Data (Text Analytics)." In Applying Methods of Scientific Inquiry Into Intelligence, Security, and Counterterrorism, edited by Arif Sari, 87-110. Hershey, PA: IGI Global, 2019. https://doi.org/10.4018/978-1-5225-8976-1.ch004

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Abstract

Text analytics applies to most businesses, particularly education segments; for instance, if association or university is suspicious about data secrets being spilt to contenders by the workers, text analytics investigation can help dissect many employees' email messages. The massive volume of both organized and unstructured data principally started from the web-based social networking (media) and Web 2.0. The investigation (analysis) of messages online, tweets, and different types of unstructured text data constitute what we call text analytics, which has been developed during the most recent few years in a way that does not shift, through the upheaval of various algorithms and applications being utilized for the processing of data alongside the protection and IT security. This chapter plans to find common problems faced when using the different medium of data usage in education, one can analyze their information through the perform of sentiment analysis using text analytics by extracting useful information from text documents using IBM's annotation query language (AQL).

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