International Journal of Advanced Technology and Engineering Exploration (IJATEE) ISSN (P): 2394-5443 ISSN (O): 2394-7454 Vol - 8, Issue - 75, February 2021
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Mining social media opinion on online distance learning issues during and after movement control order (MCO) in Malaysia using topic modeling approach

Noor Afni Deraman, Alya Geogiana Buja, Siti Daleela Mohd Wahid and Mohd Ali Mohd Isa

Abstract

The implementation of the Movement Control Order (MCO), which resulted in the closing of non-essential operations, led to the implementation of online learning at the university. This sudden announcement places university stakeholders in a state of unpreparedness to face the challenge of Open and Distance Learning (ODL). As this occurs unexpectedly and affects various people from all backgrounds, social media's views and debates need to be checked. This is necessary such that support can be given and their concerns heard, and action can be taken. This study is done by scrapping data from Facebook and Twitter with specific keywords from 17th March 2020 to 10th October 2020. A total of 2000 data were collected, but only 1283 were used after the pre-processing of the document. The results of the study show that the issues often addressed include "fees," "tired," "ODL," "information," and "zakat."

Keyword

Movement control order (MC), Open and distance learning (ODL), Opinion mining, Social media analytic, Topic modeling.

Cite this article

Deraman NA, Buja AG, Wahid SD, Isa MA

Refference

[1][1]https://www.mohe.gov.my/en/mediakpt/newspaper-cutting/1322-cabaran-pendidikan-tinggi-berdepan-impak-covid-19?showall=1. Accessed 12 October 2020.

[2][2]Arulogun OT, Akande ON, Akindele AT, Badmus TA. Survey dataset on open and distance learning students’ intention to use social media and emerging technologies for online facilitation. Data in Brief. 2020; 31:1-8.

[3][3]Dwidienawati D, Abdinagoro SB, Tjahjana D, Gandasari D. Forced shifting to E-learning during the COVID-19 outbreak: information quality, system quality, service quality, and goal orientation influence to E-learning satisfaction and perceived performance. International Journal of Advanced Trends in Computer Science and Engineering. 2020; 9(2): 1518-5.

[4][4]Shah AU, Safri SN, Thevadas R, Noordin NK, Abd Rahman A, Sekawi Z, et al. COVID-19 outbreak in Malaysia: actions taken by the Malaysian government. International Journal of Infectious Diseases. 2020; 97:108-16.

[5][5]https://www.mohe.gov.my/en/media-mohe/press-statement/1372-penangguhan-kemasukan-pelajar-baharu-dan-lama-dari-kawasan-zon-merah-covid-19-ke-ipt. Accessed 12 October 2020.

[6][6]https://www.bharian.com.my/bisnes/lain-lain/2019/01/526175/kadar-penembusan-media-sosial-malaysia-tertinggi-di-asia-tenggara. Accessed 12 October 2020.

[7][7]Kawash J, editor. Online social media analysis and visualization. Springer International Publishing; 2014:229-33.

[8][8]Reese SD, Rutigliano L, Hyun K, Jeong J. Mapping the blogosphere: professional and citizen-based media in the global news arena. Journalism. 2007; 8(3):235-61.

[9][9]https://marketingsignallab.com/social-media-marketing-statistic-in-malaysia/. Accessed 12 October 2020.

[10][10]Tribhuvan PP, Bhirud SG, Deshmukh RR. Product features extraction for feature based opinion mining using latent Dirichlet allocation. International Journal of Computer Sciences and Engineering. 2017; 5(10):128–31.

[11][11]Lamba M, Madhusudhan M. Application of topic mining and prediction modeling tools for library and information science journals. Library Practices in Digital Era. Eds. MR Murali Prasad et al. Hyderabad: BS Publications. 2018: 395-401.

[12][12]Stokes DC, Andy A, Guntuku SC, Ungar LH, Merchant RM. Public priorities and concerns regarding COVID-19 in an online discussion forum: longitudinal topic modeling. Journal of General Internal Medicine. 2020; 35(7):2244-7.

[13][13]Ankarali E, Külcü Ö. RapidMiner ile Twitter Verilerinin Konu Modellemesi. Bilgi Yönetimi.2020; 3(1):1-10.

[14][14]Ilyas SH, Soomro ZT, Anwar A, Shahzad H, Yaqub U. Analyzing Brexit’s impact using sentiment analysis and topic modeling on Twitter discussion. In the international conference on digital government research 2020 (pp. 1-6).

[15][15]Zhang H, Wheldon C, Dunn AG, Tao C, Huo J, Zhang R, et al. Mining twitter to assess the determinants of health behavior toward human papillomavirus vaccination in the United States. Journal of the American Medical Informatics Association. 2020; 27(2):225-35.

[16][16]Doogan C, Buntine W, Linger H, Brunt S. Public perceptions and attitudes toward COVID-19 nonpharmaceutical interventions across six countries: a topic modeling analysis of Twitter data. Journal of Medical Internet Research. 2020; 22(9):1-11.

[17][17]Jeong B, Yoon J, Lee JM. Social media mining for product planning: a product opportunity mining approach based on topic modeling and sentiment analysis. International Journal of Information Management. 2019; 48:280-90.

[18][18]Dahal B, Kumar SA, Li Z. Topic modeling and sentiment analysis of global climate change tweets. Social Network Analysis and Mining. 2019; 9(1):1-20.