This thesis is submitted for obtaining the Joint Master’s Degree in International Humanitarian Action. By submitting the thesis, the author certifies that the text is from his own hand, does not include the work of someone else unless clearly indicated, and that the thesis has been produced in
accordance with proper academic practices.
FACULTY OF ARTS - THE UNIVERSITY OF GRONINGEN SUBMITTED BY SHINTYA KURNIAWAN
STUDENT NUMBER: S3280691 DAY/DATE: THURSDAY, 12 JANUARY 2018
SUPERVISORS: PROF. DR. A. J. ZWITTER DR. RONAN MCDERMOTT
UNDERSTANDING INDIVIDUAL DIGITAL LITERACY
ABSTRACT
Humanitarian actors in current context rely on almost real-time information to advance and plan responses when a disaster strikes. DG ECHO, AHA-Centre, CARE, Standby Task Force, and Crisis Mappers are several groups known to monitor big data and open-sourced content for situational analysis in an emergency. However, the challenge of big-data mining lies in its quality, since not all information being monitored is relevant for disaster response management. Filtering the influx of big data requires time and resources. Furthermore, the dissemination of fake, unverifiable, and inaccurate information potentially impede the response or rescue progress, proving detrimental to the affected population. The challenge of digital divides might also conceal the needs of the most vulnerable people who do not have access or the skills to utilise technology for disaster management. Therefore, this research aims to explore whether digital-literacy skills could help internet citizens (netizens) in Jakarta to produce, distribute, and consume context-relevant information during a disaster. The result of this research will potentially serve as a reference for humanitarian actors who rely on the use of technology and user-generated content for disaster management.
ACKNOWLEDGEMENTS
At first, I was excited when I presented the thesis subject to my supervisors. In the end, I am more excited and cannot wait to submit the thesis. I would like to thank every respondent who had participated in this research and trusted me with their stories which portray the social-diversity of the Big Durian. The thesis-writing took longer than I intended to finish. Nevertheless, I treasure the learning process which reminds me that mental health well-being and feeling content are more important than grades. Thank you to the support system who reminded me to slow down and find the work-life balance every day.
I am also thankful for the guidance and direction from Prof. Zwitter who tirelessly answered every question and patiently waited for me to progress. Thank you for sharing your wisdom, as well as asking the right questions which encouraged me to do better, Andrej. A big thank also goes to Ronan, Elena, Amaranta, Jarno, Elzbieta, and the big NOHA family, who keep the global humanitarian network growing. It is an honour to be a part of this family and to meet all of you. To Ibu Lina, Mas Mizan, Pang, and colleagues at the AHA Centre, thanks for allowing me to take time off from work to refine and finish this research.
The submission of this thesis marks the end of my academic sabbatical which started in August 2015. It has been over two years of a fun and insightful adventure, which could only happen with the support of my family, friends, mentors, LPDP, and Erasmus+. My utmost gratitude goes to mami Inge, Jimmy, Nanda, Hesti, Dea, Dina, Mira, Mark, Dyen, Yudha, Mbak Siska, Lionel, Mbak Tyo, Mbak Mai, Mas Israr, Mbak Devy, Kak Laura, Myrthe, Ubo, Cory, and the NOHA Vera Cruise team. Thank you for your continuous moral support all these times.
Table of Contents
ABSTRACT I
ACKNOWLEDGEMENTS II
LIST OF ACRONYMS 2
LIST OF FIGURES AND TABLES 3
1. RESEARCH OUTLINE 4 1.1. INTRODUCTION 4 1.2. RATIONALE 9 1.3. RESEARCH QUESTION 12 2. LITERATURE REVIEW 13 2.1. DIGITAL LITERACY 14 2.2. DISASTER RESILIENCE 24
2.3. THE RELATIONSHIP BETWEEN DIGITAL LITERACY AND 30
DISASTER RESILIENCE 30
3. RESEARCH METHODOLOGY 31
3.1. FIELD RESEARCH 32
3.2. CODIFICATION 34
3.3. ETHICAL CONSIDERATIONS 36
4. FINDINGS AND ANALYSIS ON DIGITAL LITERACY 37
4.1 TECHNICAL DIMENSION 37
4.2. COGNITIVE DIMENSION 44
4.3. SOCIO-EMOTIONAL DIMENSION 50
5. FINDINGS AND ANALYSIS ON DISASTER RESILIENCE 54
5.1. ABSORPTIVE COPING CAPACITY 55
5.2. ADAPTIVE COPING CAPACITY 60
5.3. TRANSFORMATIVE COPING CAPACITY 68
6. CONCLUSION AND LIMITATIONS 73
REFERENCES 78
APPENDIX 1 83
IN-DEPTH INTERVIEW QUESTIONS: UNDERSTANDING DIGITAL LITERACY AS PART OF DISASTER
LIST OF ACRONYMS
AHA Centre: ASEAN Coordinating Centre for Humanitarian Assistance on disaster management
BMKG: Badan Meteorologi, Klimatologi dan Geofisika (National Meteorology, Climatology and Geophysics Agency)
BNPB: Badan Nasional Penanggulangan Bencana (National Disaster Management Agency) BPBD: Badan Penanggulangan Bencana Daerah (Provincial Disaster Management Agency) CCTV: Close Circuit Television
DG ECHO: Directorate General for European Civil Protection and Humanitarian Aid Operations
DRM: Disaster Risk Management
ICT: Information, Communications and Technology IDP: Internally Displaced People
IISPA: Indonesia Internet Service Provider Association OISS: Online Information Search Strategies
RPTRA: Ruang Publik Terpadu Ramah Anak (Integrated Public Child-Friendly Spaces) RT: Rukun Tetangga is a neighbourhood unit in Jakarta that includes at least 50 households RW: Rukun Warga is a community unit that is comprised of 3 to 10 RTs
SAR: Search and Rescue
SARA: An acronym of Suku, Agama, Ras, and Antar golongan – translated as ethnicity, religion, race, and inter-group association
UNISDR: United Nations International Strategy for Disaster Reduction URL: Uniform Resource Locator
LIST OF FIGURES AND TABLES
Figure 1. Types of Disasters in Indonesia in 1815- 2017 Figure 2. Types of Disasters in Indonesia in 2007- 2017
Figure 3. Conceptual Representation of a Resilient Framework Figure 4. Ng’s Digital Literacy Model
Figure 5. Reconceptualised Dimensions of Digital Literacy
Figure 6. Resilience as the result of absorptive, adaptive, and transformative capacity Figure 7. Conceptual Mind Map for Digital Literacy
Figure 8. Conceptual Mind Map for Disaster Resilience
Figure 9. General Communication Pattern of the Digital Natives in Emergency Setting Figure 10. General Communication Pattern of the Digital Immigrants in Emergency Setting
Table 1. Concepts Related to Digital Literacy Table 2. Indicators of Digital Literacy
Table 3. Indicators of Disaster Resilience
1. RESEARCH OUTLINE 1.1. Introduction
Due to its unique geographical location, Indonesia is at risk to a diverse range of disasters. There were at least 24,547 catastrophes recorded in National Disaster Management
Agency’s official database (BNPB) from 1815 to mid-2017.1 Since technological support and
disaster studies were not as developed as it is today, the presented statistics might not fully capture the actual scale and frequency of past crises. Nonetheless, BNPB’S database provides a valuable baseline for current and future risk mitigation efforts.
As seen in Figure 1, calamities which frequently occurred in the last three centuries nationwide were: floods (31.6%), tornadoes (21.4%), landslides (18.1%), fires (10.8%), and droughts (7.3%). Over the past decade, the statistic shows a similar composition with floods (31.6%), tornadoes (24.2%), landslides (19.5%), fires (10.8%), and droughts (4.8%) maintaining their dominance in Indonesia. See Figure 22 for details.
1 BNPB Republik Indonesia 2 BNPB Republik Indonesia
TERROR/SABOTAGE FLOOD
FLOOD AND LANDSLIDE HIGH TIDE/ABRASSION EARTHQUAKE
EARTHQUAKE AND TSUNAMI PEST
FIRE
FOREST AND LAND FIRES INDUSTRIAL ACCIDENT TRANSPORTATION ACCIDENT DROUGHT FAMINE EXTRAORDINARY EVENT CONFLICT/SOCIAL DISTURBANCE VOLCANO ERUPTION CLIMATE CHANGE TORNADO LANDSLIDE TSUNAMI
Based on the nationwide data presented in Figure 1 and Figure 2, flood is identified as the most-common natural disaster. Flood affects Jakarta; Indonesia’s capital city which houses key economic and governmental functions. The estimated flood-induced economic loss in
Jakarta reached up to 565 million USD in 2007 and 775 million USD in 2013.3 The earliest
mention of floods in Jakarta could be traced back to a fifth-century inscription - when the city
was part of the Tarumanegara Kingdom.4 Flood had also inundated the then Batavia
repetitiously during Dutch colonialism in the 17th-20th century.5 Historians suggest that the Dutch officials had noted the colony’s topography as a coastal low-land, including its risk as a flood-prone area. Thus, the construction of numerous canals and dams by the Dutch governance presented an early design for Jakarta as a waterfront city.6 However, insofar neither the colonial authorities nor the post-colonial government managed to thoroughly address flood risks in this region. Since Indonesia’s independence in 1945, sixteen major
floods had crippled the capital city with minor occurring sporadically on a regular basis.7
3 Wijayanti et al. 1059-1079 4 Nugroho and Yamin; Zaenuddin
5 Nugroho and Yamin; van Voorst 13; Zaenuddin 6 Zaenuddin Ch. 2
7 Nugroho and Yamin Ch. 3; van Voorst; Zaenuddin
TERROR/SABOTAGE FLOOD
FLOOD AND LANDSLIDE HIGH TIDE/ABRASSION EARTHQUAKE
EARTHQUAKE AND TSUNAMI PEST
FIRE
FOREST AND LAND FIRES INDUSTRIAL ACCIDENT TRANSPORTATION ACCIDENT DROUGHT FAMINE EXTRAORDINARY EVENT CONFLICT/SOCIAL DISTURBANCE VOLCANO ERUPTION CLIMATE CHANGE TORNADO LANDSLIDE TSUNAMI
Multiple scholars warn that climate change, increasing sea level, decreasing ground level, poor waste management, inadequate land and water use regulation, and population growth might further increase flood risks in Jakarta.8 On the other hand, the new funds9 allocated for flood-risks mitigation point towards increasing commitment as well as urgency in managing flood complications. Some of the novelties in disaster-risks management (DRM) involve the use of information, communications, and technology (ICT) which enable citizens to share data through open-sourced social media and or mobile phone applications. For example, in December 2014 to March 2015, an experimental crisis map was launched by the Jakarta Disaster Management Agency (BPBD DKI Jakarta), Twitter Inc., and SMART Infrastructure Facility - University of Wollongong. Titled petajakarta.org, the initiators
crowdsourced, mapped and relayed information of flood sites across the city.10 Peta Jakarta
successfully attracted public participation by generating 240 incoming tweets per second in average. The tweets were then computed and geo-located to create a near-real-time map which is fundamental in identifying evacuation routes by both individuals and governmental officials.
The development of Peta Jakarta was followed with the release of Qlue in 2016; a mobile phone application which aims to foster public participation in promoting governance accountability. This civic engagement application is useful in both non-emergency and emergency settings because it enables users to report local issues - such as dysfunctional public facilities, nuisances in the neighbourhood, or corrupt civil servants - to the provincial authorities. Although the application has been used on daily basis, a data inflation occurred on 20-21 February 2017 as flood inundated Jakarta. In these two days, Qlue recorded a tripled
number of reports compared to the average submissions.11
Increasingly, numerous non-state humanitarian agents have been utilising ICT when integrating grassroots participation into emergency response planning. For instance, the Indonesian Red Cross launched three mobile applications to assist public in responding to
8 Nugroho and Yamin; van Voorst; Budiyono et al.
9 The World Bank is committed to invest US$139,64 million in Jakarta Urgent Flood Mitigation Project which will end in 2019, whereas the Jakarta Provincial Authority had allocated US$53 million for flood mitigation in 2017 (World Bank; Jakarta Post)
10 Holderness and Turpin, “White Paper”; Holderness and Turpin, “From Social Media to Geosocial Intelligence” 115-133
perilous events. Each application serves a different function; Mass Rapid Assessment aims to
generate eye-witness reports from Red Cross volunteers, Siaga Bencana12 was developed as
an early-warning tool, and First Aid application provides step-by-step live-saving instructions
for early responders.13 Another tool is developed by The University of Gajah Mada and Osaka
University, namely Cared Safety Confirmation which integrates early-warning, panic button, safety guidance, reportage form, and news update into a single mobile application.14 The above-mentioned development illustrates a growing investment in ICT-based tools for humanitarian assistance in Indonesia.
Various authors acknowledge a new phenomenon in humanitarian collaboration where crowdsourced information from affected individuals complement official data which is
formally collected and published by authorised agencies.15 It appears that ICT development
may alter humanitarian protocols. Based on observations and discussions at two intergovernmental agencies’ offices, it is notable that major crisis responders equip their DRM facilities with computational tools to acquire immediate information from online sources during emergencies.16 Furthermore, reflecting on previous academic research and working opportunities at two national humanitarian agencies in Indonesia and Poland between 2012 - 2017, it is evident that humanitarian agents without similar facilities would resort to more affordable open-sourced platforms to access big data17 that is required for situational assessments. These practices showcase the humanitarians’ needs for an up-to-date information, including but not limited to the ones available on www.liveuamap.com, www.ushahidi.com, Facebook, Twitter, Google search engine or its equivalent. The question that we need to ask is, what is the accuracy and reliability of big data that humanitarian officials amass from open-sourced platforms?
Whereas quantity is ample, the quality of big data is sometimes dubious. For example, research demonstrates that approximately 75% of circulated content on Twitter in relation to
12 Translated as Disaster Preparedness
13 International Committee of The Red Cross; Meiodia 14 Universitas Gajah Mada
15 Zwitter 383-385; Memon et al.; David, Ong, and Legara; Riccardi; Meier; Yates and Paquette; Xiao, Huang and Wu; Sykes and Travis Ch.1
16 Observations and discussions were conducted during a visit to the AHA Centre in January 2015 and DG ECHO in December 2016. Both agencies showcase their surveillance facilities to monitor regional and global disasters. 17 A terminology used to refer to remarkable advances in computational processing power, information storage, and clever software programmes (Bunnik et al.)
the Boston Marathon bombing are fake tweets.18 Previous studies also underline that the propagation of false, inaccurate, or outdated information potentially reduce the trustworthiness of user-generated content.19 In contrast, Starbird et al. and Meier argue that misinformation on social media is often followed by corrective force from other users – thereby creating an organic pattern of rumours and counter-rumours distribution. Nevertheless, the following cases illustrate that misinformation in emergency settings carry risks which can hamper rescue process, waste resources, undermine the danger of crisis, and jeopardise the lives of responders or those in suffering.
The first example came from Chile when the 2010 earthquake hit. Police officers were misled by two prank tweets requesting assistance at different locations. Instead of responding to survivors trapped under the rubble, rescuers found an abandoned building and an apartment
with a couple celebrating their wedding anniversary.20 The second case study was situated in
Japan when the tsunami struck in 2011 and tweets for assistance were retweeted after the
survivors had been rescued. Moreover, the cybercascades21 of false tweets combined with the
absence of verification measures repulsed some Japanese users from accessing Twitter.22 The
third misinformation was an anti-Ebola hoax that caused the death of two persons and the hospitalisation of 20 people in Nigeria.23 The fourth case study took place promptly after two bombs exploded in Jakarta in early 2017. Some Facebook users misused the safety check feature by deploying it as an online shopping platform or requesting irrelevant assistances, such as free gasoline, new clothes for holiday, and job opportunities.24
The above-mentioned examples seem to support the assumption that there are malpractices in the provision of humanitarian big data through the inappropriate use of ICT. It is probable that such misinformation can manifest to haphazard since individuals with low
18 Meier 151
19 Alexander; Cheng et al.; Meier; Yang et al.; Riccardi 25-126; Xiao, Huang and Wu; Acar and Muraki 20 Meier 33-35
21 Cybercascades is a concept derived from social cascade theory that describes internet as a breeding ground for rapid circulation of information, including widespread popular belief without the support of reliable references (Sunstein)
22 Acar and Muraki 398
23 A broadcast message from unofficial source suggested Nigerians to drink warm salt water to prevent catching Ebola. The absence of verification to counter this message from a medical perspective has harmed some people due to overconsumption of salt water (Nababa; Neporent)
information literacy tend to accept misconstrued information as truth.25 In the light of this, one can argue that ethical digital literacy may be necessary to improve (or standardise) the quality of big data in support of emergency response efforts. Therefore, the purpose of this thesis is to explore whether digital literacy can help construct an informed society who is willing to share relevant and useful information in assisting emergency responses activities and fostering disaster preparedness. Two study groups of the population are selected as participants. The first group represents the digital natives or millennial adults26 who are over 17 years old. The second group comprised of the digital immigrants who were born in the
mid-1940s to the late-1960s.27
1.2. Rationale
Although 97,4% of Indonesian internet users are active on social media,28 research on
their behaviour during hazardous circumstances is lacking. Whereas earlier studies focus on
internet penetration and gadget ownership, further studies suggested integrating technical provision with cognitive and socio-emotional dimensions when measuring digital literacy.29
This requires a qualitative behavioural analysis if we wish to understand digital literacy as part of disaster resilience. By investigating various dimensions of digital literacy, we could review the roles of social media as a platform for continuous information proliferation during floods in Jakarta.
Furthermore, it is a commonly held view that knowledge is power30 and resilience can
be interpreted as an interplay of knowledge. 31 Thus, a better-informed society is
hypothetically more capable of transforming their knowledge into best practices when
25 Çoklar, Yaman, and Yurdakul
26 “Digital natives” is coined by Prensky to refer to the generations of people born after the 1980 whose lives immersed in digital technology. He further classifies the older generations as digital immigrants who are presumed as less adaptable towards ICT development. The age description of digital natives overlaps with the definition of millennial generation based on PEW Research Center’s demographic classification (PEW Research Center)
27 The national threshold to be considered as an adult in Indonesia 28 Indonesia Internet Service Provider Association (IISPA) 22
29 Holderness & Turpin; Jaeger et al.; Hilbert; Sharma et al.; Arke & Primack; Ng; Adigüzel qtd. in Çoklar, Yaman, and Yurdakul
30 Power/knowledge theory is a Foucauldian social notion in challenging status quo and addressing power imbalance (Foucault; Wolf)
addressing stressor or shock. Digital literacy can be considered as one contributing knowledge that can empower individuals in critical situations. However, having access to ICT infrastructure does not automatically result in transformative knowledge nor capacity.32 Therefore, the empirical study presented in this thesis aims to analyse whether the first variable could contribute to the second variable on three different dimensions: absorptive coping capacity, adaptive capacity, and transformative capacity33 – or not.
Jakarta is chosen as the research location for three reasons. First, risk analysts warn that rapid urbanisation worldwide is likely to affect more urban dwellers with increasingly
harmful economic and social consequences in the face of climate change.34 Jakarta as one of
the global megalopolitan cities suits the criteria since it is a densely populated settlement located in a high-hazards coastal area. Moreover, Jakarta was also ranked fifth on “Mind the Risk Report: a global ranking of cities under threat from natural disasters.”35 Second, Jakarta has been transitioning towards a Smart City to promote open governance and sustainable development since 2014.36 Under such circumstance, it is not surprising that the provincial government aims to integrate ICT to improve public services across sectors. This strategy is in-line with UNISDR’s suggestion which encourages the collaboration of good governance, civil society, and the private sector in addressing urban risk.37 Third, Jakarta is one of the most active cities in social media. It was crowned as Twitter Capital City in 2012 by Semiocast - a social media intelligence agency.38 It was also ranked third as the most active city on
Facebook in the second quarter of 2017, as researched by We Are Social and Hootsuite.39
Specifically, millennials and baby-boomers are selected as the niche groups of informants due to their characteristic as digital natives and digital immigrants. Prensky defines digital natives as a generation of people who were born after 1980, relying on technology in their daily lives, and are used to receiving information in a more rapid way compared with former generations. Furthermore, they also grew up with technology, comfortable with multitasking, reliant on graphics for communication, and thrive on instant gratifications and
32 Paton & Johnston; Sharma et al. 637 33 Béné et al. “Resilience Interventions”
34 UNISDR, “Risk and Poverty in a Changing Climate” 35 Sundermann, Schelske, and Hausmann
36 Pemerintah Provinsi DKI Jakarta
37 UNISDR “Making Development Sustainable” 38 Grazella
rewards.40 The previously mentioned definition intersects with PEW Research Center’s description of millennials who were born after 1980 and are more likely to identify themselves as individualists. Combining the analysis of these definitions and their familiarity with ICT, the criteria of the first niche group are Jakartans who were born after 1980, older than 17 years old, grew up with technology, presumably used to multitasking, own social media accounts, and are exposed to flood risks in Jakarta.
On the other hand, the second sample population was described as digital immigrants. Prensky coins this terminology when referring to people who were born before the 1980s and are less familiar with gadgets. However, he acknowledges that some digital immigrants can adapt faster to ICT development compared to their peers. Although they might be less familiar with gadgets, digital immigrants probably have a wider range of knowledge and experiences. They also tend to settle down at a younger age and has stronger connection towards family
values.41 In regards to age classification, PEW Research Centre develops three generational
categories for people who were born before 1980. The first one is the silent generation, born before the end of World War II. The second group is the baby boomers, born in the mid-1940s until late-1960s. The third group is Gen X, born in the mid-1960s until early 1980s.
This research will focus on the baby boomers generation as a representative of digital immigrants since their age specification intersects with the younger silent generation and the older Gen Xers. Moreover, silent generation is excluded from the analysis due to a wider generation gap between the millennials and rarer familiarity with ICT development. Data from IISPA mentions that only 10% of internet users in Indonesia aged above 55 years old (baby boomers) – yet it does not specify the numbers of internet users who are above 70 years old (the silent generation). Considering that some Gen Xers grew up in the 1980s, it is possible that they may share several characteristics with the digital natives which are less significant for comparative study. Therefore, the criteria of the second research unit are participants who were born between 1946 and 1970, might have access to internet or not, might have social media accounts or not, and are exposed to flood risks in Jakarta.
40 Teo et al. Qtd. in Çoklar, Yaman, and Yurdakul 41 PEW Research Center
1.3. Research Question
This research is designed to contribute to the knowledge of disaster resilience in urban settings. It aims to examine to which extent digital literacyaffects an individual’s capability in strengthening communal disaster resilience in Jakarta. Thereby, the primary research question is: “How does digital literacy affect individual capability in contributing to communal disaster-resilience in Jakarta?”
In order to answer the main research question, several sub-questions related to behavioural studies are developed to guide the operationalisation of the two variables:
• What are the social media habits of the population during an emergency, particularly flood?
• How does the population critically assess, produce, and distribute information on social media in the context of DRM?
• Do the participants know where to find relevant information and whom to reach out to in regards to reduce flood risks?
• Has any of the participants utilised ICT to build community’s resilience when dealing with floods?
The literature review on the next chapter is divided into two sections. The first part examines existing studies on digital literacy. The following section researches into various theories regarding disaster resilience. Both parts base the formulation of open-ended interview questions for data collection (Appendix 1). The outcome of field research and data interpretation will present a conclusion and recommendation for humanitarian big data management.
2. LITERATURE REVIEW
A systematic literature review was conducted to discover existing theoretical and conceptual frameworks regarding digital literacy and disaster resilience. Eleven academic databases42 were searched using the keywords: ‘digital literacy’, ‘disaster resilience’, ‘social resilience’, ‘digital literacy and disaster management’, and ‘disaster and social media’. Additionally, suggested readings from the thesis supervisors and secondary resources mentioned in the primary findings expand the readings for the literature review. The inclusion criteria to further specify the relevance of available resources are the publication year and the academic acknowledgement of the readings. Only publications dated from 2000-2017 and available in the formats of published academic article or book, peer-reviewed journal, official report or working paper were included in the selection. The exclusion criteria are languages and branches of science. Publications in languages other than English or Indonesian and publications related to software or computational science were eliminated from the literature review.
Deriving from the plethora of academic resources, a theoretical framework which illustrates the connection of multiple capabilities and disaster resilience is provided. According to Béné et al., a state of a resilient society is not merely a condition in the aftermath of shock or stressor. It is rather a combination of an impact of stressors, the capacities that people drew on, and attempt to deal with the aftershock at the individual, household, and
community level.43 In a similar manner, Paton & Johnston echo that people are not passive
recipients of hazard.44 They argue that during disastrous events, affected population are active interpreters of information. It is likely that people make judgments about the information they receive and interpret these messages within personally or socially constructed operative frameworks. Nevertheless, recipients of the information may interpret events differently from the senders. Thus, there is a risk of misinterpretation of hazards which needs to be corrected and a diverse range of experiences which needs to be facilitated by disaster managers.45 Therefore, one might suppose that both individual and collective capacity in understanding
42 Scopus, Science Direct, SAGE Journals, Nexis, JSTOR, Springerlink, Proquest, Project Muse, Taylor and Francis, Emerald Insight, and Web of Science
43 Bene et al. “Resilience Interventions” 11 44 Paton and Johnston 106
and verifying information might mitigate the risk of misinterpretation and contribute to the framework of resilience as presented in Figure 3.
The conceptual representation of a resilience framework on Figure 3 was developed by Béné et al. and serves as the blueprint for this research. As indicated earlier, digital literacy can be classified as part of individual and collective capacities which affect the ways people react to shocks and stressors, influencing how they adapt, recover, or transform. The theoretical conceptualisation of digital literacy and resilience will be elaborated on the next sub-sections.
2.1. DIGITAL LITERACY 2.1.1 Conceptualisation
Based on the evaluation of existing literature, the concept of digital literacy is intertwined with critical literacy, media literacy, information literacy, and social constructivism. It is possible that one may confuse the variety of concepts and use of terminologies. Therefore, the broad definitions related to digital literacy are compared in Table 1 to help identify similarities, differences, and key characteristics of this variable.
Table 1.Concepts Related to Digital Literacy
CONCEPT DEFINITION THEORIST
Digital literacy Digital literacy refers to the multiplicity of literacies associated with the use of digital technologies. These technologies are a subset of electronic technologies that include hardware and software used by individuals for educational, social and/or entertainment purposes in schools and at home that are either commercial, downloadable for trial for fixed periods of time, or are totally free and accessible from the Web.
Ng 1066
Digital literacy
as part of
information literacy
Digital literacy is a part of a broader information literacy skill which becomes a multidimensional factor that defines how to search, evaluate, and use information, and consequently has an influence on online information search strategies (OISS).
Çoklar, Yaman, Yurdakul 2-3 Digital literacy as a combination of information literacy and media literacy
Digital literacy refers to an individual’s ability to locate, evaluate, and use digital information, encompassing both technologies (e.g., computers) and services (e.g., e-mail). It can also include their ability to deal with and make sense of the amount of information they receive. Two attributes of digital literacy are information literacy and media literacy.
Jaeger et al. 5-6 Digital literacy as a mean to address digital divide.
The ability to use the Internet and new media in order to access and critically evaluate different formats and types of digital information so as to participate in the socio-economic activities of a community through digital content creation, communication and exchange. It takes into account how information needs may be fulfilled systematically. Furthermore, digital literacy is deeply entwined with the notion of digital divides.
Sharma et al. 630
Media literacy Media literacy is the ability to understand, analyze, and
evaluate media messages in a wide variety of forms.
This research reveals that teaching media literacy may help improve overall critical thinking skills.
Arke &
Primack 54,
63
Critical digital literacy
Critical digital literacy emphasises the importance of learning to recognize underlying messages in all types of resources (written, images, film, multimedia, etc.), critique them, and produce counter-narratives when engaging with online materials. It is based on the notion of critical literacy, which can be described as a process that “challenges the status quo in an effort to discover alternative paths for self and social development”.
Two key components of critical literacy are:
1. It is concerned with the social and cultural contexts in which all types of resources are both created, read or viewed.
2. It has a focus on practical action and community engagement.
McNicol 233
Social
constructivist digital literacy
Digital literacy is a mastery of technology tools and digital practices to activate participation in online cultures and contexts. Social constructivist digital literacy is a human-centred conceptualisation of
digital literacy which builds upon theoretical
perspectives that view human as an autonomous agent who holds a productive purpose driving technology use, for instance, the design and creation of a concrete artefact or product. This concept proposes a skills-based model centring on an integrated set of task-driven computing activities supported by social constructivist theory.
Reynolds 736-737
Reflecting on the theoretical matrix in Table 1, there are several recurring characteristics associated with digital literacy. Those are skills/ability/mastery/capability, information, digital technology, critical thinking, participation/engagement, individual and social development, cultures, and context. Considering these attributes, we might suggest that digital literacy is the capacity in which individuals critically assess information that they received, distributed, and produced on various digital media platforms. Potentially, this capacity can manifest into active participation for personal and social development. In the context of this research, the development aspect relates to disaster resilience.
A distinctive approach is found in Arke & Primack’s research which focuses on conventional types of information sources when measuring media literacy, i.e., print media, radio, and television. The authors seem to perceive participants as merely recipients and evaluator of information, thus undermining the participants’ (re)creative capacity. Notwithstanding, Arke & Primack acknowledges the need to assess new (digital) media literacy in relations to the growing media convergence which opens wider opportunities for users’ participation. Specifically, they suggest future researchers to develop ways of assessing emotional aspects of media literacy, since media consumption can be an emotional experience,
for instance regarding political and persuasive communication.46 It seems probable that using
digital media during a crisis can also be an emotional experience.
On a critical note, some researchers tend to equate digital literacy with gadget ownership and internet penetration.47 Although infrastructure availability is an initial step to build a knowledge society, there are two major drawbacks with this simplification. Firstly, it overlooks the difference between access to information with skills to transform knowledge into practices. Secondly, it overgeneralises participation through digital platforms as a positive attribute. Hence, failing to recognise both sides of the coin namely, ethical and harmful participation. It must therefore be assumed that infrastructure provision might be insufficient to generate positive outcomes. Having the tools to access information is not the same as obtaining and distributing the required knowledge using the given infrastructure in a socially constructive manner. As mentioned by Sharma et al., an information society is based on infrastructure, while a knowledge society builds on this to encompass participation and hence
46 63-64
47 Holderness & Turpin; Jaeger et al.; Hilbert; Sharma et al.; Arke & Primack; Ng; Adigüzel qtd. in Çoklar, Yaman, and Yurdakul
inclusion. Therefore, when assessing digital literacy, it is crucial to envision a digital-literate population as a knowledge society, beyond information society. One might suppose that digitally-literate person is characterised as an individual who has access to ICT infrastructure and complements this privilege with the knowledge to utilise the physical attribute for positive purposes.
In relations to Sharma et al.’s thesis about knowledge society, Spangenberg suggests that one of the pillars of a knowledge society is education and training.48 He underpins the importance of digital learning as an interaction between students and educators – facilitated through online as well as offline infrastructure. In contrast, Jones, Johnson, & Gruszczynska argue that education and training may not be sufficient to construct meaningful digital literacy. Building on Prensky’s thesis of digital natives and digital immigrants, they argue that educators (as digital immigrants) do not always know better about technology than learners (digital natives). Their essay pinpoints the evolutive nature of ICT development, which makes both students and educators strive to find solutions to tackle the risk of privacy violation or to address digital divides. Faced with such a situation, it is clear that there is room to investigate how different generations adapt to ICT innovation and achieve digital maturity.
In addition, Jones, Johnson, & Gruszczynska suggest that high level of participation in social networking sites indicates digital maturity. Their paper does not ascertain the differentiation between constructive and destructive participation. All the studies reviewed so far constrain digital literacy in classroom settings. None of them elaborated digital literacy within disaster response context. Given this information, it would be interesting to explore how the respondents of this research experience learnings beyond formal education settings to obtain ethical digital literacy skills that could be useful for floods responses in Jakarta. Of all the reviewed literature, Adigüzel49 and Ng offer two well-structured conceptualisations of multi-dimensional digital literacy. Therefore, the next sub-chapter mainly based on their theorisation.
48 Qtd. In Sharma et al.
49 Qtd. in Çoklar, Yaman, and Yurdakul. The original work was written in Turkish, therefore, it is inevitable to use the secondary source.
2.1.2 Dimensions
In this section, two theories and one concept were reviewed to recognise multiple dimensions of digital literacy. The first concept proposes four dimensions of information literacy which are: 1.) the capability in defining information needs, 2.) having access to
information, 3.) capacity to use the information, and 4.) ethical and legal use of information.50
The first capability reflects individual’s knowledge in identifying what type of information is required in which situation. The second dimension relates to capacity and availability of means to reach the required information. The third dimension demonstrates one’s potential to convey information for problem-solving. The fourth dimension showcases the evaluative
skills of participants when using the information.
Correspondingly, Ng develops a digital literacy model with three dimensions as illustrated in Figure 4. The first dimension signifies one’s technical ability to use ICT devices. For instance, a person can be considered technically capable if she/he understands how to operate a mobile phone, plug an earphone, install application, download or upload files to a shared folder. The cognitive dimension reveals how technical capabilities can assist human beings to generate, evaluate, create or recreate useful information from various digital resources. Some indicators of this dimension include knowing where to search for information and what type of software is required to perform the intended function. Finally, the socio-emotional dimension defines how an individual use ICT in a sensible way to foster collaboration and share learnings. The last dimension is associated with netiquette and protective behaviour in the cyber realm, such as knowing what type of information is to be disclosed and how to take security measures when being threatened online.
Moreover, Ng mentions that multiple literacies are integral with the cognitive dimension. In a more comprehensive sense, Ng’s explanation can be examined from a media development perspective. Formerly, when the industrial revolution catalysed the birth of press and printed media, readers are encouraged to develop textual and visual analytical skill. Later, since the radio was invented, the verbatim and auditory senses of listeners became key when consuming news. Especially, when radio was utilised as a propaganda tool during World War II. Thereafter, the presence of televisions stimulates both textual, visual, and audio sensitivity. These experiences contribute to one’s meaning-making processes. However, since the internet enables media convergence, it offers multi-media content that develops in various formats or combination of formats. Additionally, the internet also comes with new types of data and features, e.g.: location tag, emoji, and commentary boxes. This development demands an amalgamation of expertise if one aims to possess a solid digital literacy skill. It is therefore reasonable that Ng stresses:
“The individual should have an understanding of multiple literacies to help
them decode information that are text-based as well as information from images, sound bytes (e.g. podcasts), videos, maps and models – these involve multiliteracies skills that are linguistic, visual, audio, spatial, gestural (as captured in videos) and multimodal (as in multimedia resources).”51
There are several resemblances between Adigüzel’s proposal and Ng’s model. Although the terminology varies, some of these dimensions overlap with one another. Ng’s conceptualisation seems to offer a more comprehensive approach. However, Adigüzel’s explanation can help expand the indicators of digital literacy. Contrasting their objectives and analysis, Adigüzel’s first and third dimension can be classified as the cognitive dimension in Ng’s model. Moreover, the description of his second dimension is similar to the technical dimension in Ng’s model. Finally, the ethical and legal use information is embodied in socio-emotional dimension. Reflecting on this analysis, a digital literacy model combining both theories is presented in Figure 5.
51 Ng 1068
Capability in defining information needs and capacity to use the information
Ethical and legal use information Having access to
information
Although both theorists emphasised that critical literacy should blanket all dimensions of digital literacy, neither Adigüzel nor Ng detail the indicators of critical literacy or ways to develop such skill. Arguably, digital literacy is not limited within the scope of content analysis. It would be ideal if one can complement content validity with source credibility in the context of critical literacy during disastrous events. In the light of this, one may refer to a simple communication theory which comprises of three elements: sender, channel to distribute messages, and receiver.52
If digital literacy is constrained within the content analysis, it can be interpreted that the existing concept of digital literacy fails to acknowledge the other two elements of communication: the sender and the receiver. This brings back the argument that human beings are not passive recipients and are capable to decode information and respond to messages. Meier identifies, during Arab Spring the journalism principle was effective when investigating clues and triangulating content from social media. This practice was deployed by one Egyptian journalist who refused to believe dubious breaking news alerts on Twitter.53 Putting these observations together, it would appear that a classic journalism principle 5W+1H might improve the conceptualisation of digital literacy. The 5W+1H concept stands for what, when, where, who, why, and how. It covers a broader aspect of information verification since it considers the identity of news sources, including any agenda it carries.
2.1.3. Indicators
To contextualise the traits of digital literacy in disaster context, several indicators are developed based on the analysis on the previous sub-section. The indicators include - but not limited to - the ones presented in Table 2.
52 Shannon and Weaver
Table 2. Indicators of Digital Literacy DIMENSIONS INDICATORS T ec hni ca l
Ability to operate technological devices, such as a smartphone (Android, IOS, Blackberry)
Ability to operate technological features, such as:
- email (send/reply/forward messages, attach document) - instant messenger (i.e., WhatsApp, Blackberry messenger)
- social media accounts (e.g., Facebook, Twitter, Instagram, Path, YouTube)
- social media tools (e.g., privacy setting, Facebook safety check, Facebook live, Insta Story, Retweet button, Like button)
- online map services or application (e.g., Google map, Waze)
- producing accurate textual/audio/visual content for citizen journalism in an emergency (e.g., BBC iWitness, Net TV Citizen Journalism)
Ability to use mobile phone application related to DRM (e.g.: Qlue, Siaga Bencana)
Cogni
ti
ve
Capability to define information needs and act accordingly for disaster risk reduction (e.g., evacuation route, emergency contact numbers, rainfall intensity, early warnings)
Capability to reach out to the right authority through ICT when necessary (e.g., addressing inquiry to BPBD’s official Twitter account, provincial Search and Rescue team, or Jakarta Fire Brigade)
Capability in verifying news content and sources during emergency (e.g., recognising edited photo, identifying the timeliness of a picture, differentiating verified social media accounts with the fake accounts) Capability to utilise geotag feature for rescue purposes (e.g., share location to family members through instant messenger when in danger)
S oc io -e m ot iona l
Willingness to react to inaccurate or misleading information in emergency setting. For example:
- flag inaccurate content on social media during an emergency - report fake news sources to authorities in an emergency setting
- evaluate privacy setting for protective measures during an emergency - review personal digital footprint after the disaster had passed
Hesitation to misuse ICT for mischievous behaviour in an emergency setting. For example:
- fabricate or proliferate false news in emergency - commit fraud during an emergency
- create/share inappropriate jokes during a critical situation
- create/share audio-visual documents of affected population or disaster victims which could dehumanise or jeopardise their well-being
2.2. DISASTER RESILIENCE 2.2.1 Conceptualisation
Etymologically, resilience is derived from the Latin word resilīre which means to leap back or recoil.54 Theoretically, the early conceptualisation of resilience evolves from ecological and psychological studies.55 From an ecological perspective, resilience is perceived as a physical attribute or a system which allow individuals to reclaim equilibrium when their situation is destabilised by shocks.56 The shocks in question are possibly generated from individual, political, social, and environmental changes – e.g., climate change, plague, election outcome, divorce, natural disasters, the death of a family member, cancer, or decline of income.57 Reviewed from a psychological theory, resilience is acknowledged as an individual’s capacity in retaining their emotional health during adversity and escape through it undamaged. In terms of mental-health well-being, resilience is also associated with protective factors. 58
MacLean et al. observe that psychological scholars tend to contrast resilience with vulnerabilities, whereas the ecological literature affiliate resilience with flexibility, adaptive capacity, and durability. On the other hand, Béné et al. propose a different approach in
54 Partridge
55 MacLean et al.; Barnes & Hall 56 Barnes & Hall
57 Kwok et al.; Barnes & Hall; Manyena 58 MacLean et al.; Barnes & Hall
contextualising resilience for DRM. They argue that resilience and vulnerability is not a double-ended linear structure, but rather a cyclical process.59 Furthermore, they suggest that it would be more useful to consider resilience as an intermediary outcome instead of a final objective within a restrictive band between resilience and vulnerability. Manyena’s observation underpins this argument, he warns that:
“Outcome-oriented disaster resilience programmes are inclined to adopt
command and control styles that risk preserving the status quo, and which might entrench exclusion, and take attention away from the inequality, oppression and entitlement loss that results in cases of proneness to insecurity and disaster.”60
Moreover, Manyena notices that when disaster resilience is viewed as an outcome, there is a tendency to deploy DRM in a traditional reactive sense which generally assumes the affected populations as mere beneficiaries. Alternatively, he advises resilience to be approached as a process within a human-centred adaptive framework. The latter practice might assist disaster managers in empowering affected population to become active decision makers when addressing disaster risk. In addition to the adaptive capacity which Manyena underlines, Béné et al. offer a more comprehensive theory by adding two dimensions into resilience: absorptive and transformative capacity.
2.2.2 Dimensions
As illustrated in Figure 6, Béné et al. 61 assess the concept of resilience beyond coping objectives and re-emphasise several attributes that are associated with resilience, such as stability and flexibility. By evaluating these attributes, they manage to offer a three-dimensional narrative of resilience which includes absorptive coping, adaptive, and transformative capacity. In the first dimension, absorptive coping capacity indicates individuals and or households’ capability to adopt numerous disaster mitigation strategies for survival purposes. This capacity is reflected by individuals and families’ ability to fulfil their basic needs when disaster strikes, e.g., water, food, shelter, sanitary facility. Second, the
59 Bene et al. “Resilience Interventions” 60 Manyena 438
adaptive capacity signal any capacity to learn, adjust and integrate interdisciplinary knowledge to re-attain equilibrium immediately. Flexibility is determinant of this dimension. The final dimension is transformative capacity which extends any surviving and re-stabilising skills into a creative force. This dimension can manifest in the forms of: capacity to modify infrastructure, strengthen social protection, and influence regulations to enhance the personal and communal protective measures when confronting any upcoming adversities.
Although each dimension can operate independently, it shall not be interpreted that all three dimensions are mutually exclusive. Béné et al. observe that sometimes all three dimensions can appear simultaneously and are interconnected to each other. However, the transformative capacity is typically constructed during the post-disaster phase. This tends to indicate that the quality of transformative capacity might affect the other two dimensions and put into test when a similar disaster re-occurs in the future.
Despite their complex conceptualisation of resilience, Béné et al. notice a research gap regarding contributing factors to resilience capacity.62 They mention that although the factors seem to be growing, research availability in this area is limited. Differs from that, MacLean et al. suggest knowledge sharing and social learning be assessed as part of resilience. The
62 Bene et al. “New Utopia or New Tyranny?” 16
findings of this thesis may attempt to fill the existing literature gap. Furthermore, the reviewed papers deconstruct multiple layers of resilience at the individual, household, neighbourhood, community, organisational, district, national, or a wider ecosystem level.63 It has been suggested that resilience at a level greater than community may involve the analysis of pre-existing economic, political, social and cultural capital, along with demographic and risk
knowledge analysis.64 It is beyond the scope of this research to conduct a thorough analysis
of the abovementioned factors at municipal, provincial or national level. Hence, this research primarily focuses on assessing resilience at the individual and communal level since these two stages relate closer one to another. Specifically, the measured communal level is known as Rukun Warga (RW) in Jakarta.
Since resilience is perceived as an intermediary outcome, more tangible indicators which signal the impact of resilience will be mentioned. From previous research,65 several attributes are associated with communal resilience, such as:
• Clear structure of leadership • Social support
• Trust
• Human capital, e.g., trained personnel for medical or rescue efforts • Communal disaster simulation on regular basis
• Community space and amenities (food and non-food items) • Community participation
• Democratic and collaborative decision-making process • Communal resources mapping
• Disaster management planning
• Voluntary public awareness campaign • Emergency skills training
• Funding availability for disaster response
63 Béné et al. “Resilience Interventions”; MacLean et al.; Kwok et al. 64 Kwok et al. 200
On top of that, reflecting on previous experiences and observations during flood responses, there are more indicators which can be integrated into the existing literature. For example, provision of an early warning system, well-structured communication network and communication flow, well-managed social networking forum for RT members (e.g., a Facebook group for RT members), or availability of rescue and evacuation equipment (safety jackets, inflatable boat). The detailed indicators are presented in Table 3.
2.2.3. Indicators
From examining the theoretical reviews, several indicators to identify various dimensions of disaster resilience are listed in Table 3. It is noteworthy to mention that most of the indicators are situated in emergency settings – except the ones signifying the transformative dimension which focus more on recovery phase in the post-disaster setting. The following list of indicators will help guide the categorisation of responses from participants. However, not all indicators should be present to legitimise the existence or strength of a dimension.
Table 3. Indicators of Disaster Resilience
DIMENSIONS INDICATORS A bs orpt ive Copi ng
Capability to fulfil basic needs for survival, such as:
- procure clean water during disaster/ availability of clean water - sustain food security (access and preserve food) during disaster/
availability of food for individual and household’s needs - access latrine and other WASH facilities during a disaster - access medical assistance during a disaster – if necessary - mitigate hazardous risk in regards to safety and security standard - find an adequate shelter for family members and RT members
A da pt ive Ca p ac it y
Capability to improve individual and communal well-being during an emergency, includes but is not limited to:
- organising a communal response team in an emergency - organising a communal kitchen in an emergency
- organising or accessing communal medical services in an emergency
- providing and maintaining a functional communal WASH facility
- facilitating edutainment needs for children in emergency/ availability of a child-friendly space in an emergency
- monitoring and communicating the ongoing disasters risk to RT members during an emergency
- operating evacuation infrastructure during an emergency
- providing sufficient mental health care for community members - distributing logistics justly to community members in
emergency
Capability to identify and address the needs of most vulnerable groups during emergency (e.g., lactation room for pregnant women, access for wheelchairs for elderly and handicapped community members)
T ra ns form at ive Ca p ac it y
Participatory mechanism to establish or strengthen communal DRM plan. For example:
- Opportunity to engage in post-disaster evaluation planning - Availability of a participatory communal DRM plan with clear
leadership structure and job descriptions
- Availability of an accountable feedback mechanism for decision makers regarding DRM plan
- Availability of disaster risks map – covering insights from all community members
- Non-discriminative communal resources mapping/ inclusive list of trained personnel for medical or rescue efforts at RT
- Availability of disaster simulation schedule & first aid training Voluntary public awareness campaign to inform RT members about DRM plan
The use of ICT to maintain communication network of RT members in relation to DRM plan, e.g.: cleaning rota, maintenance schedule, etc
2.3. THE RELATIONSHIP BETWEEN DIGITAL LITERACY AND DISASTER RESILIENCE
Reflecting on the above-mentioned literature review, it is clear that digital literacy can be perceived as a capacity that may help individuals in responding to a stressor or shock, including but not limited to natural disasters. As illustrated in Figure 3., digital literacy can be a contributing factor to help increase individuals’ skills in addressing and recovering from a shock. Possessing the skills to utilise digital platform to source the right information might help flood-affected community members ameliorate sufferings and prevent further loss. At the transformative dimension, the experiences and knowledge acquired from both online and offline resources have the potential to help mitigate risks and construct individual/communal resilience.
Drawing on the previous literature, I propose that individual digital literacy may manifest into communal resilience through knowledge sharing and social learning at three different phases of DRM: before, during, and after a disaster takes place. The ability to make use of various mobile applications and internet-based features may or may not help community members to reduce flood-risks in their area. Thereby, several hypotheses are developed as follow:
H0: digital-savvy individuals are potentially more resilient than digital-illiterate
individuals during a critical situation.
H1: digital-savvy individuals are potentially as vulnerable as the digital-literate
individuals during a critical situation.
H2: digital-illiterate individuals from older generations are not necessarily more
vulnerable than the digital-savvy groups. Especially if they possess a wider range of experiences and skills developed in the pre-internet era.
H4: disaster resilience is not affected by digital literacy or by age, but can be influenced
The findings indicate that individual digital literacy does not seem to affect communal disaster resilience significantly since other factors are involved, i.e., leadership, fellowship, and collective interests in DRM. However, digital literacy may accelerate the speed of coordination and responses to address a critical situation. Furthermore, although the digital literacy of the younger participants is more advanced compared to the older ones’ in general, having the technical capability to use ICT tools does not automatically transform the users into effective disaster managers.
3. RESEARCH METHODOLOGY
Reflecting on the rationale (1.2), research objective (1.3), and the literature review (Chapter 2), a comparative qualitative approach was chosen as the methodology to answer the research question. Multiple scholars suggest qualitative methodologies for data collection if the nature of a research is explorative and empiricist.66 According to Lamont, an empirical research method is characterised by naturalism, behaviourism, and explanatory traits. Moreover, he mentioned that an empirical approach would be most useful if a researcher aims to explain events, developments, or the behaviour of involved actors in regards to the research topic. Additionally, an empiricist research methodology might be instrumental in revealing
under-researched practices.67 On top of that, Mayring mentions that a qualitative approach is
more appropriate to analyse a cyclical process. As mentioned in the theoretical review, ICT development and disaster resilience are rather cyclical instead of a linear process. Therefore, a comparative study is utilised to explore how members of different generations use technology when a flood takes place and whether it contributes to a communal disaster resilience or not.
According to Poerwandari, open-ended questions are instrumental to pursue deeper insights regarding a specific case study. Therefore, a set of open-ended interview questions (see Appendix 1) is designed for the participants who wish to share their experiences when using ICT during floods in Jakarta. Information from participants was coded and analysed with QCA Map68 to formulate an inductive data analysis. The reliability of the data is then
66 Babbie; Lamont; Mayring; Poerwandari 67 Babbie Chapter 10; Lamont; Poerwandari
68 QCA Map is an open-source software for qualitative content analysis which enables researchers to conduct open coding, axial coding, and selective coding on an online platform.
tested referring to four criteria for qualitative studies: credibility, transferability, dependability, confirmability.69
Daymon and Holloway mentioned that the construct credibility of a qualitative field research is strengthened when readers find the relevance of the topic within their social context. On the other hand, Poerwandari underlines that the credibility of qualitative research can be supported by the availability of research evidence, such as interview transcripts, recordings, and an accountable coding process. Whereas credibility replaces internal validity, transferability substitutes external validity and is related to the replicability of the same research instrument for different population or settings.70 The third criterion is dependability which relates to the consistency of interview structure and external audit. It has been suggested for external auditor(s) to step in and review the process of qualitative data collection and analysis to increase the dependability of a research design.71 For this reason, Prof. Dr. Andrej Zwitter who is the main thesis supervisor, Dra. Endang Setiowati M.Si who is a social research specialist, and Mira Caliandra MA who is a psycho-social researcher in disaster context, had helped evaluated the interview questions prior to the field research. The final criterion is confirmability which can be demonstrated by assessing whether the interview results had answered the expressed research question or not.72 In correspondence with confirmability, Poerwandari suggested that qualitative researchers conduct communicative validation which can be done by reaffirming the post-analysis data representation with the participants. Thus, all participants were given the opportunities to confirm or refine the data analysis presented in Chapter 4 - to avoid subjective assumptions or misinterpretation. Written approvals from participants are manifested on signed consent forms.
3.1. Field Research
The field research took place between 9 – 25 September 2017. Nine semi-structured in-depth interviews were conducted with 10 different participants to identify habitual patterns of information-searching and information-sharing in disaster contexts. Considering the technical feasibility and comfort of participants, the native Indonesian language became the
69 Daymon and Holloway; Poerwandari 70 Daymon and Holloway
71 Daymon and Holloway
