Understanding Responses to Worship Regulations in the Pandemic Era: Text Data Mining Analysis in the Indonesian Context

被引:1
|
作者
Adil, Muhammad [1 ]
Huda, Miftachul [2 ]
机构
[1] Univ Islam Negeri Raden Fatah, Dept Islamic Studies, Palembang 30126, South Sumatra, Indonesia
[2] Univ Pendidikan Sultan Idris, Fac Human Sci, Tanjong Malim 35900, Perak, Malaysia
关键词
supportive; contradictive; worship regulations; pandemic age; discourse analysis; detailed proper translation; better understanding; behavior change; COVID-19; TRAUMA;
D O I
10.3390/rel14040549
中图分类号
B9 [宗教];
学科分类号
010107 ;
摘要
This paper aims to examine the critical discourse on responses to worship regulations during the coronavirus (COVID-19) pandemic. Diverse responses emanated from the media, religious leaders, and civil society organizations in the Indonesian context. The wide range of responses to worship regulations is reflected in continuous debate, demonstrating two primary groups, one in support of the government regulations and the other opposed to limitations on congregational worship activities. This shows the need for the proper messaging of content and dissemination to promote behavioral changes relative to relevant health issues. In order to achieve the main objective, we employed a qualitative method involving a discourse analysis of several leading online news sources' viewpoints, religious leaders' viewpoints, and religious organizations' public statements. This study found two main factors associated with the response to worship regulations in the pandemic era. The main finding involved supportive and contradictive orientations. The supportive path indicated a supportive response, referring to the enhancement of the proper analysis of public worship regulations, while the contradictive one referred to the continuation of life as normal, free of restrictions and regulations. This study suggests that clear details on the reasons for restrictions and regulations are required on all forms of social media in order to provide all parties with a better understanding of the need for these measures.
引用
收藏
页数:19
相关论文
共 50 条
  • [1] Data Analysis Support by Combining Data Mining and Text Mining
    Matsumoto, Tomoya
    Sunayama, Wataru
    Hatanaka, Yuji
    Ogohara, Kazunori
    2017 6TH IIAI INTERNATIONAL CONGRESS ON ADVANCED APPLIED INFORMATICS (IIAI-AAI), 2017, : 313 - 318
  • [2] Knowledge Entity Extraction and Text Mining in the Era of Big Data
    Zhang, Chengzhi
    Mayr, Philipp
    Lu, Wei
    Zhang, Yi
    Data and Information Management, 2021, 5 (03): : 309 - 311
  • [3] A text mining approach for CSR communication: an explorative analysis of energy firms on Twitter in the post-pandemic era
    Rocco Mazza
    Emma Zavarrone
    Mirko Olivieri
    Daniela Corsaro
    Italian Journal of Marketing, 2022, 2022 (3) : 317 - 340
  • [4] Understanding water disputes in Chile with text and data mining tools
    Herrera, Mauricio
    Candia, Cristian
    Rivera, Diego
    Aitken, Douglas
    Brieba, Daniel
    Boettiger, Camila
    Donoso, Guillermo
    Godoy-Faundez, Alex
    WATER INTERNATIONAL, 2019, 44 (03) : 302 - 320
  • [5] Opinion Mining and Sentiment Analysis Need Text Understanding
    Delmonte, Rodolfo
    Pallotta, Vincenzo
    ADVANCES IN DISTRIBUTED AGENT-BASED RETRIEVAL TOOLS, 2011, 361 : 81 - +
  • [6] The need for a better understanding of context when applying CITES regulations: The case of an Indonesian parrot - Tanimbar corella
    Jepson, P
    TRADE IN WILDLIFE: REGULATION FOR CONSERVATION, 2003, : 153 - 159
  • [7] An Analysis of Data Mining and Application in the Era of Big Data
    Zhang, Yue
    Du, Li
    2018 5TH INTERNATIONAL CONFERENCE ON ELECTRICAL & ELECTRONICS ENGINEERING AND COMPUTER SCIENCE (ICEEECS 2018), 2018, : 284 - 288
  • [8] Internet public informatioan text data mining and intelligence influence analysis for user intent understanding
    Wu, Shaofei
    JOURNAL OF INTELLIGENT & FUZZY SYSTEMS, 2020, 38 (01) : 487 - 494
  • [9] Understanding Customers Using Facebook Pages: Data Mining Users Feedback Using Text Analysis
    Wu, Hsin-Ying
    Liu, Kuan-Liang
    Trappey, Charles
    PROCEEDINGS OF THE 2014 IEEE 18TH INTERNATIONAL CONFERENCE ON COMPUTER SUPPORTED COOPERATIVE WORK IN DESIGN (CSCWD), 2014, : 346 - 350
  • [10] Public reactions to e-cigarette regulations on Twitter: a text mining analysis
    Lazard, Allison J.
    Wilcox, Gary B.
    Tuttle, Hannah M.
    Glowacki, Elizabeth M.
    Pikowski, Jessica
    TOBACCO CONTROL, 2017, 26 (E2) : e112 - e116