International Journal of Social Science & Economic Research
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Title:
STORIES UNFOLD: ISSUES AND CHALLENGES ON DATA PRIVACY USING LATENT DIRICHLET ALLOCATION ALGORITHM

Authors:
Jeffrey C. Cinco

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Jeffrey C. Cinco
Leyte Normal University, Philippines

MLA 8
Cinco, Jeffrey C. "STORIES UNFOLD: ISSUES AND CHALLENGES ON DATA PRIVACY USING LATENT DIRICHLET ALLOCATION ALGORITHM." Int. j. of Social Science and Economic Research, vol. 3, no. 1, Jan. 2018, pp. 347-360, ijsser.org/more2018.php?id=21. Accessed 2018.
APA
Cinco, J. C. (2018, January). STORIES UNFOLD: ISSUES AND CHALLENGES ON DATA PRIVACY USING LATENT DIRICHLET ALLOCATION ALGORITHM. Int. j. of Social Science and Economic Research, 3(1), 347-360. Retrieved from ijsser.org/more2018.php?id=21
Chicago
Cinco, Jeffrey C. "STORIES UNFOLD: ISSUES AND CHALLENGES ON DATA PRIVACY USING LATENT DIRICHLET ALLOCATION ALGORITHM." Int. j. of Social Science and Economic Research 3, no. 1 (January 2018), 347-360. Accessed , 2018. ijsser.org/more2018.php?id=21.

References
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Abstract:
An emerging trend in the cyberspace is called data privacy that is often unattended and ignored by Netizens. This paper looks into available documents found in journals, news articles and published reports to understand and uncover hidden issues and challenges about data privacy. These documents were extracted and processed using web mining technique and methods using topic modeling of Natural Language Processing (NLP). This study utilized Latent Dirichlet Allocation Algorithm (LDA) using R-programming. LDA is an unsupervised machine learning that has the capability to generate latent themes from the collected text documents or corpus. As a result, five latent themes were identified based on the result and a profound understanding of how data privacy affects the internet society nowadays.