Social Media and Crisis Communication

Social media communication is an important element in dual screening practice as this behavior emerges after being facilitated by online platforms (Barnidge et al., 2017). Video viewers use another screen to obtain more information beyond the content they watch (Gil de Zuniga et al., 2015) and to share the information they have acquired (Chadwick et al., 2017). As individuals watch videos on one screen, they usually utilize another screen to react to the video content through online media, such as social media (Atifi & Marcoccia, 2017). Dual screeners also interact on social media by making comments online, looking at what other people post, and having conversations in real time (Cameron & Geidner, 2014).

The rise of social media has altered the way people respond to a crisis situation. Individuals across the globe use social media to convey their thoughts and feelings regarding crises (Terpstra et al., 2012). Open social micro-blogging platforms, such as Twitter, are increasingly utilized by people from many countries to create and disseminate content as crisis responses in various ways, ranging from positive responses (e.g., calling social support or assistance for resilience, giving advices, and sharing information), to more social disruptive responses (e.g., spreading fake news, rumor, and negative comments) (Burnap et al., 2014).

The recent KM bombing case in Jakarta on May 2017, also sparked extensive reactions on social media, especially Twitter. Twitter was the first platform used to broadcast news about this bombing (Sodikin, 2017). The users kept using this platform to update the situation and post

DOI:10.6814/THE.NCCU.IMICS.006.2018.F05 pictures from the location (Yunus, 2017). Aside from sharing information pertaining to the event, some users also utilized Twitter to show their social support, such as expressing condolences or offering prayer to the fallen victims (Pangerang, 2017).

Twitter use in crisis communication has attracted some scholars to investigate the online discussions on this platform during crisis situations. Acar and Muraki (2011) examined the types of contents shared through Twitter during an earthquake and tsunami in Japan. The findings indicated the similarity of tweets posted on the affected and non-affected areas and most contents on Twitter were related to warnings, calling for help or assistance, and updates regarding the events. Bruns et al. (2012) investigated the patterns of conversations on Twitter as responses to the 2012 Queensland flood, which identified five categories: direct experience, help and fundraising, media sharing, discussions and reactions, and information. Heverin and Zach (2010) also analyzed tweets about the shooting of police officers in Seattle and found some types of contents on this platform, for instance emotion-related, information-related, and action-related tweets. Bautista and Lin (2015) also investigated tweets pertaining social support messages for the victims of #Fallen44 in the Philippines and identified three main codes: informational support (i.e., posting or sharing pictures, posting or sharing news articles, posting or sharing personal comments, providing status updates, posting or sharing videos, asking questions), emotional support (paying tribute, expressing sympathy, offering prayer, expressing grief and shock), and non-social support (spamming, expressing anger, expressing humor).

With the increased popularity of Twitter, users utilize this platform differently and each person might play a different role within this digital network (Jackson & Welles, 2016). One of the most important role is influencers or mobilizers. These mobilizers are crucial as they have the ability to influence the diffusion of messages and to shape digital conversations (Albalawi &

DOI:10.6814/THE.NCCU.IMICS.006.2018.F05 Sixsmith, 2015). They can frame the online conversations by attracting the public’s attention to a certain issue and enforce their agenda to the public (LeFebvre & Armstrong, 2016).

Past studies use various indicators to identify these mobilizers, such as the numbers of followers (Romero et al., 2011; Quercia et al., 2011) and also the interactions, such as retweets, replies, and mentions (Boyd et al., 2010). Lefebvre and Armstrong (2016) used these two indicators to identify the mobilizers during crisis situations by analyzing users who had great numbers of followers and retweets. They then categorized them into several types of mobilizers, including key mobilizers (users that post a lot of tweets and generate a great amount of retweets), unwitting mobilizers (users that post tweets once or twice, but generate a great amount of retweets), moderate influencers (users that actively post tweets and generate quite a lot of retweets), and passionate participants (users that keep tweeting but cannot generate a lot of retweets).

Retweet is an important aspect of Twitter as Liu et al. (2014) suggests that retweets is currently taking over the original content. Retweet could serve as a validation to someone else’

thoughts (Boyd et al., 2010). Thus, the higher retweets someone gets, the higher power that he/she can mobilize other Twitter users. However, this current study adjusted Lefebvre and Armstrong’s (2016) digital participants’ categories by expanding ways to classify engagement from just retweets to replying and giving favorites. Therefore, these three types of interactions are accumulated to measure the engagement of audience, replacing the original definition of generating retweets only. The definition of the categories after the adjustments used in this study are key mobilizers (active Twitter users with high engagement rate), unwitting mobilizers (tweeting occasionally with high engagement rate), moderate influencers (active Twitter users with quite high engagement rate), and passionate participants (tweeting frequently with low engagement rate). However, the Twitter content analysis performed in this study elaborates more

DOI:10.6814/THE.NCCU.IMICS.006.2018.F05 on identifying the most influential users on the social media conversations based on their engagement rate.

In addition to digital participants, there are other groups of public who are affected by the crisis occurrence, for instance incident-related actors (people who are directly affected by the situations, such as survivors and their family and friends, witnesses, bystanders, and so on) and the local journalists who report the events (Tandoc & Takahashi, 2016). These three groups with different roles have various levels of involvement in a crisis. Incident-related actors, especially the survivors and affected residents are the most affected group by the incident. In addition, journalists are involved in an incident by reporting the happenings objectively for working purposes. During a crisis, journalists that play a role of detached observers have the time pressure to seek information and report latest and accurate news for audiences. Although journalists have to be objective and professional on the field, they are still affected by the pressure and tragedies on the locations (Berrington & Jemphrey, 2003). Furthermore, the effects of a crisis, like terrorist attacks, go beyond geographic boundaries (Shaluf et al., 2003) and thus it can affect public in general. The active public then reacts to the crisis using social media (Liu et al., 2011) and categorized as digital participants. Figure 1 illustrates the different levels of involvement among different crisis groups.

Starting from the center and moving to the outer rim, it implies the most influenced by the crises or terrorist attacks to the least influenced. Taking into account of these levels of involvement, this investigation attempts to explore and find the differences and similarities of different groups’

media behaviors during stages of crisis communication process (i.e., observation, interpretation, choice, dissemination) and their motives as well as the use of dual screening.

DOI:10.6814/THE.NCCU.IMICS.006.2018.F05 Figure 1. Crisis groups with varying involvement

Less involved

DOI:10.6814/THE.NCCU.IMICS.006.2018.F05 CHAPTER 3

METHOD

This exploratory study takes a mixed method approach to conduct Twitter content analysis and semi-structured in-depth interviews to answer the following three research questions:

RQ1. What patterns of terrorism-related social media communication were shown during the terrorist attack (i.e., the KM bombing attack) based on the Twitter content analysis?

RQ2. During different stages of the crisis response process, what kinds of media behaviors did Indonesian dual-screeners from various groups perform during the terrorist attack?

RQ3. What motivated Indonesians from various groups to use dual screening during terrorist attacks (e.g., affective, cognitive, and social motives)?

The advantages of this integrative research design include enabling researchers to obtain comprehensive and holistic understanding of the area of the enquiry, to seek the answers for different research questions, to enrich the diversity of perspectives as by combining both researchers’ and respondents’ views, and to enhance the credibility of the findings (Bryman, 2008).

The mixed method approach of Twitter content analysis and in-depth interview has been widely used by many scholars (Anagnostopoulos et al., 2017; Schreiner, 2018; Vobič et al., 2017). The meshing of data from Twitter content analysis and qualitative analysis generated from the interviews can complement each other and result in comprehensive and insightful understanding of dual screening crisis communication. Twitter content analysis can provide Indonesians’ social media crisis responses during terrorist attacks, while the qualitative data from the interviews can explore individuals’ experiences, particularly their dual screening use during terrorist attacks (Kinnison et al., 2017).

DOI:10.6814/THE.NCCU.IMICS.006.2018.F05 Therefore, to answer the RQ1, the content analysis was conducted to understand the social media communication by examining contents on Twitter, the major social media in Indonesia, during the terrorist attack. Aside from examining the prevalent messages on social media, the content analysis also analyzed the key mobilizers or the most influential users on Twitter and helped identify the digital participants recruited for the following step of the study, in-depth interview. Next, to answer RQ2 and RQ3, semi-structured interviews were employed to explore Indonesians’ media behaviors in different stages of the crisis response process and their motivations to use dual screening during terrorist attacks.

Content analysis of tweets is a technique that allows researchers to investigate information and content patterns in texts, including tweets (Small, 2011). Twitter content analysis can be used to monitor numerous events happening in public (Gul et al., 2016) and to show communication patterns (Ogan & Varol, 2017). Past Twitter content analysis research also examined online discussions during crises, such as the study by Acar and Muraki (2011) on the response of Japan’s tsunami case, Heverin and Zach’s (2010) examination of Twitter’s discussion about violent crisis in the Seattle-Tacoma, Washington, and Bruns et al.’s (2012) investigation on Twitter’s conversations regarding the South East Queensland Floods.

This study focuses on analyzing the social media communication on the major platform in Indonesia, Twitter. It is often used as a conversational platform to discuss many social issues and political events (Gul et al., 2016). Twitter, as an open platform, allows citizens to express their viewpoints. Sometimes, anti-government content was disseminated on Twitter when traditional media, due to licensing issues, did not cover such news under censorship constraint (Ogan & Varol, 2017). With more than 50 million users, Twitter is an important online platform in Indonesia used to discuss various topics, especially during crisis situations. Jakarta, the capital of Indonesia, is

DOI:10.6814/THE.NCCU.IMICS.006.2018.F05 recognized as the world’s most active city on Twitter (Lipman, 2012). In 2016, Indonesian users posted more than 4.1 billion tweets (Ador, 2016). Furthermore, as Twitter users utilize hashtags to associate the content of their messages to intended or established topics (Kongthon et al., 2012), analyzing a myriad of relevant tweets under key hashtags is a way to understand netizens’

perspectives in responding to specific topics.

This present study employed Twitter content analysis to understand Indonesians’ social media communication regarding the KM bombing attack by investigating the trends and prevalent messages of tweets in three types of emotion-related, information-related, and action-related contents under the framework of Heverin and Zach (2010). Twitter content analysis also identified the most influential digital participants on Twitter during the KM bombing attack which also helped recruit the interviewees for the next step of the study.

The second part of the mixed method study is the in-depth interviews with Indonesian dual-screeners who have used dual screening the KM bombing attack. Qualitative research method is

“an attempt to tap the deeper meanings of particular human experiences and are intended to generate qualitative data” (Rubin & Babbie, 2011, pp. 437). It allows researchers to acquire meaningful and fruitful insights about a social phenomenon (Attride-Stirling, 2001) and make sense of the process of that phenomenon (Rubin & Babbie, 2011). It has been a popular method utilized in crisis and risk communication (Austin et al., 2012; Hale et al., 2005; Yates & Partridge, 2015). Qualitative methodology often uses interviews to gather the qualitative data (Padgett, 2017). Interview is a conversation between two or more people with a particular structure and goal determined by the interviewer (Kvale, 2007), in order to obtain wealthy and complex information (Cavana et al., 2001). In-depth interview enables researchers to explore participants’ experiences to gain deeper understanding of their viewpoints and meaning construction (Kvale & Brinkmann,

DOI:10.6814/THE.NCCU.IMICS.006.2018.F05 2009). As this study attempts to understand dual screeners’ experiences in media use during a bombing crisis, in-depth interviews are an appropriate method to be employed here.

This study conducted in-depth interviews with Indonesians dual screeners by recruiting digital participants identified through the Twitter content analysis by sending them personal messages on Twitter. Although this platform is the largest social media used for crisis communication during terrorist attacks (Listiyani, 2017), Twitter is not the only channel. As this study aimed to understand the motivations and media behaviors of Indonesian dual screeners along the crisis communication responses process during the KM bombing attack, the recruitment of interviewees went beyond only Twitter users. Thus, this research also recruited other affected groups (incident-related actors and local journalists covering the KM bombing) suggested by Tandoc and Takahashi (2016).

3.1. Data collection

3.1.1. Twitter content analysis

For the data mining, this study utilized the Python library Tweepy to connect directly to Twitter streaming API. This study focused on tweets using the hashtag #KamiTidakTakut that emerged quickly after the attack and was consistently used for the KM bombing incident. The duration of tweet collection is from May 24, 2017, when KM bomb detonated until June 5, 2017, when the conversations subsided. The total number of tweets collected is 7,685. Python library Tweepy is also able to retrieve the metadata of the tweets which will be useful for this study, for instance the username, date, numbers of retweets, numbers of favorites, texts of the tweets, locations, mentions, hashtags, and permalinks.

DOI:10.6814/THE.NCCU.IMICS.006.2018.F05 During the preliminary analysis, this study identified that most of the tweets were in Indonesian and a small amount were in English, French, Japanese, Thai, and Korean. As the coders were able to understand multiple languages, all tweets in Indonesian and English were analyzed directly while tweets in other languages were analyzed after translation. After further identification, some tweets in Japanese and in Thai were not posted by Indonesians and as this current study attempted to explore how Indonesians responded toward the terrorist attack, the tweets posted by non-Indonesians were eliminated from the analysis. The preliminary analysis also identified irrelevant tweets from the dataset. Irrelevant tweets to the KM bombing were mostly advertisements, discussions about other topics, or jokes. In total, there were 584 tweets removed after identifying the language of the tweets and irrelevant tweets, leaving 7,101 tweets for further analysis.

This study also identified the Twitter mobilizers based on their engagement rate (retweet, reply, favorite). LeFebvre and Armstrong (2016) distinguished four types of digital participants on social media participation during protests or emergency: key mobilizers, unwitting mobilizers, moderate influencers, and passionate participants. In Twitter content analysis, this study focused more on identifying the most influential users based on their engagement rate and listed the top 15 mobilizers which mostly belong to the categories of key mobilizers and unwitting mobilizers. This study also utilized the examination of the digital participants to recruit the interviewees for the next step of the study. However, most participants belonging to these categories were mostly the government institutions/ individuals or security forces while this study would like to understand the dual screening experience of the public’s dual screening use. Thus, this investigation also identified other digital participants who used dual screening to discuss about KM bombing attack to be recruited for the in-depth interviews.

DOI:10.6814/THE.NCCU.IMICS.006.2018.F05 3.1.2. In-depth Interview

This research conducted in-depth interviews with the different affected groups: incident-related actors (survivors and their family members/friends and affected residents), digital participants, and journalists who covered the terrorist attack. In total, there are 21 Indonesian dual screeners from the three aforementioned groups interviewed in this study. Each group consisted of seven respondents. There are some other criteria to be fulfilled by the participants. All respondents must be active dual screeners who own at least two screen devices (TV, smartphone, laptop, tablet, and so on). Moreover, they should have prior experiences of dual screening use during the KM bombing case in May 2017. Users aged 20 to 35 are most active dual screeners (SWAonline, 2017) and major social media users in Indonesia (Emarketer, 2016), which is the age selection criterion for interviewees.

The purposive and snowball sampling was employed to recruit the respondents of this study. However, there are different recruitment methods for each respondent group for recruiting the digital participants, the first-step Twitter analysis was used to identify dual screeners on Twitter. As previously mentioned, the in-depth interview recruited digital participants who discussed KM bombing attacks. The most influential users on Twitter such as the top 15 key mobilizers were primarily government-related institutions or individuals, thus they did not fulfill the criteria. Interview invitations were sent to Twitter users belonging to these categories through Twitter direct messages or tweets. Moreover, for the journalists group, the researcher observed the online articles or videos about the KM bombing that appeared on Twitter and contacted the reporters to be interviewed. These journalists then referred other journalists who also had reported the incident. To assure the variability, each journalist could only refer another person. These

DOI:10.6814/THE.NCCU.IMICS.006.2018.F05 journalists work for different media, including TV, online news portals, and newspapers. Lastly, to recruit the incident-related actors, the researcher observed activities on social media and also announced the recruitment information on these platforms. People who responded to the advertisement were contacted to schedule the interview.

Prior to the interview, all respondents must sign the consent form (see Appendix A). They were allowed to terminate the interview process if they felt uncomfortable. All collected data from the interviews was treated as confidential information as this study only used personal data for research purposes only. To protect the personal data, the respondents of this study were under name codes (I for incident-related actors, D for digital participants, J for journalists). There were 34 questions for the interview to answer the three proposed research questions and covered four aspects: filtering questions, demographic questions, motivations of dual screening use, and crisis responses of terrorist attacks. The questions were also translated into Indonesian by the researcher and another Indonesian speaker was recruited to recheck the translation to ensure the meaning was not altered (see Appendix B). Each interview took place for around 30 to 60 minutes and the conversations were audio recorded for transcription and analysis. This research had the interview guides in English and Indonesian. All interviews transcripts in Indonesian were translated into English. Along with the researcher, another Indonesian speaker was recruited to recheck the translation in order to ensure the meaning of the conversations was not lost or altered in translation.

The participants were offered IDR 50,000 phone credit as the incentive.

DOI:10.6814/THE.NCCU.IMICS.006.2018.F05 3.2. Data analysis

3.2.1. Twitter data analysis

There are at least seven steps in the process of content analysis, including “formulating the research questions to be answered, selecting the sample to be analyzed, defining the categories to be applied, outlining the coding process and the coder training, implementing the coding process, determining trustworthiness, and analyzing the results of the coding process” (Shieh & Shannon, 2005, pp. 1285). To develop the code scheme, this study employed a hybrid approach, combining inductive and deductive approach to the coding (Fereday & Muir-Cochrane, 2006). By implementing this approach, the code scheme has a balance of existing framework (deductive

There are at least seven steps in the process of content analysis, including “formulating the research questions to be answered, selecting the sample to be analyzed, defining the categories to be applied, outlining the coding process and the coder training, implementing the coding process, determining trustworthiness, and analyzing the results of the coding process” (Shieh & Shannon, 2005, pp. 1285). To develop the code scheme, this study employed a hybrid approach, combining inductive and deductive approach to the coding (Fereday & Muir-Cochrane, 2006). By implementing this approach, the code scheme has a balance of existing framework (deductive