ABSTRACT
Purpose: Zakat (Islamic almsgiving) plays a considerable role in dealing with the socioeconomic issues in times of COVID-19 pandemic, and such roles have been widely discussed in virtual events. This paper aims to discover knowledge of the current global zakat administration from virtual events of zakat (e.g. webinars) on YouTube and Zoom via text mining approach. Design/methodology/approach: The authors purposefully sampled 12 experts from four different virtual zakat events on YouTube and Zoom. The automated text transcription software is used to pull the information from the sampled videos into text documents. A qualitative analysis is operated using text mining approach via machine learning tool (i.e. Orange Data Mining). Four research questions are developed under the Word Cloud visualisation, hierarchal clustering, topic modelling and graph and network theory. Findings: The machine learning identifies the most important words, the relationship between the experts and their top words and discovers hidden themes from the sample. This finding is practically substantial for zakat stakeholders to understand the current issues of global zakat administration and to learn the applicable lessons from the current issues of zakat management worldwide. Research limitations/implications: This study does not establish a positivist generalisation from the findings because of the nature and objective of the study. Practical implications: A policy implication is drawn pertaining to the legislation of zakat as an Islamic financial policy instrument for combating poverty in Muslim society. Social implications: This work supports the notion of "socioeconomic zakat”, implying that zakat as a religious obligation is important in shaping the social and economic processes of a Muslim community. Originality/values: This work marks the novelty in making sense of the unstructured data from virtual events on YouTube and Zoom in the Islamic social finance research. © 2022, Emerald Publishing Limited.
ABSTRACT
Purpose: Zakat (Islamic almsgiving) plays a considerable role in dealing with the socioeconomic issues in times of COVID-19 pandemic, and such roles have been widely discussed in virtual events. This paper aims to discover knowledge of the current global zakat administration from virtual events of zakat (e.g. webinars) on YouTube and Zoom via text mining approach. Design/methodology/approach: The authors purposefully sampled 12 experts from four different virtual zakat events on YouTube and Zoom. The automated text transcription software is used to pull the information from the sampled videos into text documents. A qualitative analysis is operated using text mining approach via machine learning tool (i.e. Orange Data Mining). Four research questions are developed under the Word Cloud visualisation, hierarchal clustering, topic modelling and graph and network theory. Findings: The machine learning identifies the most important words, the relationship between the experts and their top words and discovers hidden themes from the sample. This finding is practically substantial for zakat stakeholders to understand the current issues of global zakat administration and to learn the applicable lessons from the current issues of zakat management worldwide. Research limitations/implications: This study does not establish a positivist generalisation from the findings because of the nature and objective of the study. Practical implications: A policy implication is drawn pertaining to the legislation of zakat as an Islamic financial policy instrument for combating poverty in Muslim society. Social implications: This work supports the notion of “socioeconomic zakat”, implying that zakat as a religious obligation is important in shaping the social and economic processes of a Muslim community. Originality/values: This work marks the novelty in making sense of the unstructured data from virtual events on YouTube and Zoom in the Islamic social finance research. © 2022, Emerald Publishing Limited.
ABSTRACT
Purpose: Zakat during the COVID-19 outbreak has played a vital role and has been significantly discussed in the virtual environment. Such information about zakat in the virtual world creates unstructured data, which contains important information and knowledge. This paper aims to discover knowledge related to zakat administration during the pandemic from the information in a virtual environment. Furthermore, the discussion is contextualised to the socio-economic debates. Design/methodology/approach: This is a qualitative study operated via text mining to discover knowledge of zakat administration during the COVID-19 pandemic. The National Board of Zakat Republic of Indonesia (BAZNAS RI) is selected for a single case study. This paper samples BAZNAS RI’s situation report on COVID-19 from its virtual website. The data consists of 40 digital pages containing 19,812 characters, 3,004 words and 3,003 white spaces. The text mining analytical steps are performed via RStudio. The following R packages, networkD3, igraph, ggraph and ggplot2 are used to run the Latent Dirichlet Allocation (LDA) for topic modelling. Findings: The machine learning analysis via RStudio results in the 16 topics associated with the 3 primary topics (i.e. Education, Sadaqah and Health Services). The topic modelling discovers knowledge about BAZNAS RI’s assistance for COVID-19 relief, which may help the readers understand zakat administration in times of the pandemic from BAZNAS RI’s virtual website. This finding may draw the theory of socio-economic zakat, which explains that zakat as a religious obligation plays a critical role in shaping a Muslim community's social and economic processes, notably during the unprecedented times of COVID-19. Research limitations/implications: This study uses data from a single zakat institution. Thus, the generalisation of the finding is limited to the sampled institution. Practical implications: This research is both theoretically and practically important for academics and industry professionals. This paper contributes to the novelty in performing text mining via R in gaining knowledge about the recent zakat administration from a virtual website. The finding of this study (i.e. the topic modelling) is practically essential for zakat stakeholders to understand the contribution of zakat in managing the COVID-19 impacts. Social implications: This work derives a theory of “socio-economic zakat” that explains the importance of a zakat institution in activating zakat for managing socio-economic issues during the pandemic. Thus, paying zakat to an authorised institution may actualise more maslahah (public interest) compared to paying it directly to the asnaf (zakat beneficiaries) without any measurement Originality/value: This study is among the pioneers in gaining knowledge from Indonesia’s zakat management during the COVID-19 outbreak via text mining. The authors’ way of analysing data from the virtual website using RStudio can advance Islamic economics literature. © 2021, Emerald Publishing Limited.
ABSTRACT
Purpose: Despite the COVID-19 recession, the collection of zakat (almsgiving) managed by the National Board of Zakat Republic of Indonesia (BAZNAS RI) has increased, especially during Ramaḍān 1441 Hijra. Previous works show a positive relationship between digital zakat campaign and zakat collection. This paper aims to study the means of digital zakat campaign during COVID-19 outbreak. This topic is theoretically and practically important in the emerging debate of Islamic marketing, notably in Islamic social finance field. Design/methodology/approach: This paper uses a qualitative research approach. A case study is engaged in the selection of BAZNAS RI for a detailed discussion of a zakat organisation. Meanwhile, a netnographic approach is used to analyse the number of 549 posts from BAZNAS RI’s social media, which are Facebook, Instagram, Twitter and YouTube. Furthermore, a qualitative software analysis of NVivo 12 Plus is used in performing the analytical procedures. Findings: This work explains the means of digital zakat campaign during COVID-19 outbreak with a case of BAZNAS RI. It is identified the number of 6 parent nodes and 64 child nodes from the analysis using NVivo 12 Plus. The authors’ parent nodes are “donation”, “infaq” (Islamic spending for charities), “Ramaḍān matters”, “ṣadaqah” (voluntary charity), “virtual events” and “zakat”. These nodes detail digital campaign of BAZNAS RI posted in its social media during COVID-19 period in Ramaḍān. A theoretical implication of inclusive marketing is derived from the analysis. It explains that the inclusiveness of digital contents is practically significant in campaigning zakat as a religious obligation that contributes to social and financial benefits. Research limitations/implications: This paper does not claim a positivist perspective on the relationship between digital zakat campaign and zakat collection. Instead, this paper explores in-depth the practice of digital zakat campaign, which the previous study confirms its association with a muzakki’s (Muslims who are obliged to pay zakat) decision to pay zakat. Practical implications: This paper establishes the Islamic marketing theory that is derived from industrial practices. The inclusiveness of digital contents in zakat campaign is critical in activating zakat as a religious obligation that authentically shapes the social and economic processes of a Muslim community. This theory is practically important for 'amils (employees) of zakat institution who work in the marketing division, chiefly to create such contents to post in social media. Social implications: The authors’ node of zakat distribution for COVID-19 relief indicates the importance of a formalised zakat institution to actualise zakat’s role in handling socioeconomic problems. Thus, paying zakat formally in an authorised organisation may contribute to a greater social contribution and maṣlaḥah (public interest) than paying it informally without any effective measurement. Originality/value: This study contributes to the novelty in the Islamic marketing debate within two folds. First, this paper is among the pioneers in studying digital zakat campaign during COVID-19 outbreak by using a netnographic approach. Therefore, a theoretical implication derived from industrial practices is contributed. Second, this paper details the steps in using NVivo 12 Plus to analyse the unstructured data sampled from the internet. The future studies may thus refer to this work to understand the application of netnography and the procedures in analysing data from social media using this software. © 2020, Emerald Publishing Limited.