General Information
    • ISSN: 1793-8201 (Print), 2972-4511 (Online)
    • Abbreviated Title: Int. J. Comput. Theory Eng.
    • Frequency: Quarterly
    • DOI: 10.7763/IJCTE
    • Editor-in-Chief: Prof. Mehmet Sahinoglu
    • Associate Editor-in-Chief: Assoc. Prof. Alberto Arteta, Assoc. Prof. Engin Maşazade
    • Managing Editor: Ms. Mia Hu
    • Abstracting/Indexing: Scopus (Since 2022), INSPEC (IET), CNKI,  Google Scholar, EBSCO, etc.
    • Average Days from Submission to Acceptance: 192 days
    • E-mail: ijcte@iacsitp.com
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Editor-in-chief
Prof. Mehmet Sahinoglu
Computer Science Department, Troy University, USA
I'm happy to take on the position of editor in chief of IJCTE. We encourage authors to submit papers concerning any branch of computer theory and engineering.

IJCTE 2018 Vol.10(4): 116-120 ISSN: 1793-8201
DOI: 10.7763/IJCTE.2018.V10.1210

The Application of Text Mining and Analytics Studies: A Systematic Literature Review

Shahid Shayya, Shamshul Bahri, Noor Ismawati Jaafar, Ainin Sulaiman, Seuk Wai Phoong, and Wai Chung Yeong

Abstract—A large amount of textual data is generated everyday through information technology, especially by social media platforms such as social network sites and mobile instant messaging applications. To analyse these large amount of textual data, analysts often turn to techniques called text mining and text analytics. Unfortunately, studies using these techniques are often more occupied with developing a new or extended models rather than determining how the findings could benefit organizations or societies. This occupation with the techniques rather than how the techniques could benefit the organizations or societies at large may render these studies a “plaything for the data scientists” rather than a useful technique to enhance knowledge and improve practice. This study intends to remedy this imbalance by identifying studies that use text mining and analytics techniques to inform organizational and societal practices. To do so, we will employ a method called the systematic literature review (SLR). The technique contains explicit and systematic process that distinguishes it from the conventional literature review. Eventually, the study reveals the source of data of the selected studies, their application area and the parties that will benefit from their findings. Lastly, this study discusses how studies using text mining and analytics can provide benefits to the larger society.

Index Terms—Text analytics, text mining, systematic literature review, application.

Muhammad Shahid Shayya is with the Berkshire Media Private Ltd, First Avenue Bandar Utama, 47800 Petaling Jaya, Selangor, Malaysia (e-mail: shahid@berkshiremedia.com.my). Shamshul Bahri, Noor Ismawati Jaafar, Sulaiman Ainin, Seuk Wai Phoong, and Wai Chung Yeong are with the Department of Operations and MIS, Faculty of Business and Accountancy, University of Malaya, 50603 Kuala Lumpur, Malaysia (e-mail: esbi@um.edu.my, isma_jaafar@um.edu.my, ainins@um.edu.my, phoongsw@um.edu.my, yeongwc@um.edu.my).

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Cite:Shahid Shayya, Shamshul Bahri, Noor Ismawati Jaafar, Ainin Sulaiman, Seuk Wai Phoong, and Wai Chung Yeong, "The Application of Text Mining and Analytics Studies: A Systematic Literature Review," International Journal of Computer Theory and Engineering vol. 10, no. 4, pp. 116-120, 2018.


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