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Article

Public Trust in the Time of Pandemic: An Analysis of Social Networks in the Discourse of Large-Scale Social Restrictions in Indonesia

Department of Political Science, Faculty of Social and Political Sciences, Universitas Padjadjaran, Jatinangor 45363, Indonesia
Soc. Sci. 2023, 12(3), 186; https://doi.org/10.3390/socsci12030186
Submission received: 22 January 2023 / Revised: 8 March 2023 / Accepted: 13 March 2023 / Published: 18 March 2023
(This article belongs to the Special Issue Contemporary Local Governance, Wellbeing and Sustainability)

Abstract

:
This article discusses public trust in the Indonesian government’s response to the COVID-19 pandemic, explicitly focusing on the discourse surrounding large-scale social restrictions (LSSR). In a time of uncertainty, the public requires timely and actual information, most of which is gathered through online media, with Twitter being one such medium. This article applies social network analysis to examine how information about the restrictions is shared and discussed on social media platforms and how this discourse may impact public trust in government institutions in the first phase of pandemic handling. Although LSSR is the government’s policy, this study shows that the interpersonal network plays a more significant part in distributing information, indicating a legitimacy crisis of formal and authoritative sources of information. The negative sentiment voiced by critics did not show public rejection of the implementation of LSSR. On the contrary, what was implied by those critics was public doubt against the consistency and firmness of LSSR implementation—because of this, restoring public trust requires planned information management to communicate risks to those who are affected by LSSR implementation, as well as managing negative sentiments that arise as a response.

1. Introduction

The coronavirus disease, or COVID-19, became a trending topic that was most talked about at the beginning of 2020 and continues today as the post-pandemic discourse emerges in online and offline conversations. Conversations on COVID-19 in social media cover broader issues such as anxiety; government response; social and economic effects of the social distancing policy; hoaxes regarding the source of coronavirus, to the point of doubting the existence of coronavirus and asking whether the virus is part of a conspiracy scheme; and debate on the efficacy of vaccination (The Guardian 2020). This diversity shows how COVID-19 has affected all dimensions of human life in various parts of the world.
COVID-19 is a public issue at a global level, the handling of which is not enough to confine it within a particular country’s territorial borders, thanks to its rapid transmission pattern. The world has gone through various plagues caused by viruses such as HIV, H1N1, SARS, MERS, and Ebola, but COVID-19 has a different character than those viruses, so many countries do not have adequate preparation to respond to the spread of COVID-19. In coming times, along with social and economic dynamics, risks of pandemics are estimated to be possible. Implementing physical distancing to limit the virus’s spread reinforces the public’s tendency to use global social networks such as Facebook or Twitter to facilitate human interaction and share information regarding the virus (Ali et al. 2019; Oh et al. 2020; Westerman et al. 2014). On the other hand, the prevalence of hoaxes amidst uncertain times, and the information overload in social media, can weaken responses against the virus and even sow public distrust against the government (Garrett 2020; Jang and Baek 2019).
Governments are expected to swiftly formulate and implement policies that can respond to the dynamics of the developing situation in various impacted sectors. This effort will be effective only if there is public support to obey protocols and policies that have been implemented, which calls for a relevant communication style amidst this pandemic. The concept of legitimacy has shifted in the context of the distribution and reception of messages through social media platforms (Limaye et al. 2020). The public tends to believe information from their relationship circle instead of authoritative sources, including the government or other formal institutions. This pattern differs from the traditional pattern, with exceptional knowledge and accountability mechanisms to guarantee that the spread of information is verified (Eysenbach 2007). In the context of the COVID-19 pandemic, the first model of information legitimacy is more robust, along with the increased public need for timely and actual information. This tendency became a crucial link for government actions which will determine the effectiveness of the COVID-19 response, since implementing health protocol alone is not enough; also required are efforts to build public trust in the effectiveness of policies that are made.
Indonesia is a country with the fourth-largest population in the world, and is predicted to be one of the countries that will face a significant impact from COVID-19 for a prolonged time, compared with other countries with less population than Indonesia (Djalante et al. 2020). Since the official announcement on 2 March 2020, the total number of positive cases of COVID-19 has reached 6,735,451, with 6,570,963 recovered, 160,905 dead, and 900 suspects (https://covid19.go.id/id/artikel/2023/02/25/situasi-covid-19-di-indonesia-update-25-februari-2023s, accessed on 25 February 2023). The total number of positive cases still shows an upward trend, even though the government launched a COVID-19 vaccination program in 2021. One of the initial efforts made by the Indonesian government in limiting the spread of the COVID-19 virus was imposing restrictions on mobility through the Pembatasan Sosial Berskala Besar (PSBB) policy, for further reference in this article translated to Large-Scale Social Restrictions (LSSR).
This mobility restriction policy was chosen to show how public trust in the government was formed during the initial period of handling the COVID-19 pandemic. The debate on regional quarantines is not confined to Indonesia since it is also found in other countries. In the global conversation sphere, the lockdown issue is faced with herd immunity (Jenkins 2020). The timing of restrictions in each country has varied. Various countries such as Spain, Austria, Italy, China, Germany, and the United States, that implemented lockdowns through suppressive or less coercive mitigation policies, have improved their condition so that these countries have relaxed their lockdowns. Herd immunity is letting the virus spread, intending to build individual immunities so they may fight off the virus. The debate between lockdown and herd immunity grew after the lockdown was enacted, while in the early phase before the implementation of the lockdown such debate did not exist. The condition differs in Indonesia, where the debate on the need for regional quarantine was initiated as a public demand.
The implementation of LSSR is a case in which the public, through discussions on online media, encouraged the government to enact concrete policies to limit the spread of the COVID-19 virus after the first case was officially recognized. Initially, the central government rejected the implementation of the lockdown because of fears it would have an impact on slowing economic activity. LSSR implementation started with the local government closing schools and public places. After local governments took similar steps in big cities in Indonesia, such as Jakarta, West Java, Banten, and Central Java, the President issued regulation named Government Regulation Number 21, established in 2020, which became the legal basis for LSSR. Through this legal basis, local governments limited the movement of people and goods in and out of their respective areas after obtaining permission from the relevant ministries, in this case, the Ministry of Health.
After launching the policy in April 2020, conversations in the Indonesian online media show exciting dynamics. From February 2020 until May 2020, conversations regarding COVID-19 were filled with debates on the issues of the use of masks, the implementation of lockdown, LSSR, and the effectiveness of policies, as well as government programs to handle the economic and social repercussions of COVID-19. The debate on enacting regional quarantine is one of the issues that attracted a large amount of attention. API Twitter data processing shows that the lockdown issue attracted engagements from 12,147 tweets from 5 April 2020 to 14 May 2020 (https://academic.droneemprit.id/#/search/view/analysis/media/id/848, accessed on 14 May 2020), while 268,792 tweets followed the conversation on LSSR over the same period (https://academic.droneemprit.id/#/search/view/analysis/media/id/849, accessed on 14 May 2020).
Twitter API tracing found a tweet from the account @KawalCOVID19 on 28 March 2020 as one of the accounts that initiated the discussion on lockdown through its thread regarding the urgency of regional quarantine (https://twitter.com/KawalCOVID19/status/1243920510628425729, accessed on 12 May 2020). This tweet was aimed at the account @Jokowi, the personal account of President Joko Widodo, and also several other personal accounts of regional leaders in Java, that is, the accounts of Anies Baswedan (governor of DKI Jakarta), Ridwan Kamil (governor of West Java), Ganjar Pranowo (governor of Central Java), and Khofifah Indar Parawansa (governor of East Java). Since posting for the first time, this tweet has been retweeted 6397 times and liked 5860 times. This tweet garnered the most engagement in the discussion regarding the lockdown in Indonesia. The account @KawalCOVID19 is an account that civilian volunteers manage that is composed of medical professionals who aim to serve updates on COVID-19 data (https://twitter.com/KawalCOVID19, accessed on 12 May 2020).
The discussion on lockdown subsided and shifted to the issue of LSSR when the government officially permitted the governor of DKI Jakarta to enact LSSR to limit the spread of coronavirus. The same decision was also given to the governor of West Java and other regions with a high rate of COVID-19 cases. Since the beginning of April 2020, online discussions have been filled with discussions on implementing LSSR. The initial momentum came from the enactment of Keputusan Presiden Nomor 11 Tahun 2020 (Presidential Decree Number 11, established in 2020), which established a state of public health emergency concerning coronavirus in Indonesia, which was later followed by the enactment of Peraturan Pemerintah Nomor 21 Tahun 2020 (Government Regulation Number 21, established in 2020) that governs the implementation of LSSR in facing COVID-19. Even though the reiterations of government positions facing COVID-19 were made through these regulations, online debates concerning the effectiveness of LSSR did not subside. These debates are fascinating to observe since the discussions cover the health and political perspectives, especially concerning the government’s capacity to handle the virus’s spread and the social restrictions’ other effects. The issue of government capacity not only filled online discussions in Indonesia but in other countries facing the same issue during a pandemic (Maxwell 2003; You et al. 2017). This means the public’s interest is not only related to their health, but also to the social dimension management that arose out of the handling of the virus, that required government authority in its decision-making.
This study highlights how the dynamics of conversations on Twitter can be a force to encourage governments to take concrete steps to limit people’s movements during the early days of the pandemic. Analysis of online discussion dynamics can yield an image of the public perspective on the issue of LSSR, mainly because this issue directly impacts the public’s daily lives. The enactment of LSSR will lead to individual activity restrictions in the public sphere, such as education, work, and other kinds of mobility. On a larger scale, this restriction will also result in enterprises grinding to a halt, especially in sectors that do not serve basic public needs. The handling of COVID-19 faces a dilemma between prioritizing health and prioritizing the economy because the restrictions imposed to halt infection rates negatively impact the economic sector, specifically those in the lower to middle classes (Yumna et al. 2020).
The dilemma of prioritizing health or the economy has filled public discussions, including online discussions, since the start. The social and economic effects of the handling of COVID-19 mean that this pandemic is more than just a health issue, but is also a political issue, since there is a debate on policy options to be taken and implemented by the government. The messages sent through social media reflect public aspiration and how various sides frame the issue of LSSR. Framing has been the central power instrument to compete in introducing the meaning of a phenomenon (DeLuca et al. 2012; Paskarina and Nuraeni 2021; Pieri 2019; Wang et al. 2020). The enactment of LSSR is a government choice that attempts to bridge the differences between the need to preserve public health from virus infection on one side, and maintaining the economic sector, especially parts with a direct connection to basic needs. The option of implementing several restrictions on public activity will make way for a debate on how far such a policy could be implemented for the public interest. The effectiveness of LSSR implementation is determined by the government’s ability to build public trust in the policy option that is made.
This article examines public trust in the Indonesian government’s response to the COVID-19 pandemic, explicitly focusing on the discourse surrounding large-scale social restrictions during the early phase of the virus spreading (March to May 2020). During the initial phase of the spread of COVID-19, from March 2020 to mid-2021, the government did not respond quickly and thoughtfully to the spread of this virus and even showed a denial tendency and prioritization of economic concerns over public health measures (Mietzner 2023). Indonesia was once ranked the third country in the world with the most additional daily cases of COVID-19 in early July 2021 (https://www.kompas.com/tren/read/2021/07/08/073500365/menilik-posisi-kasus-covid-19-di-indonesia-dibandingkan-dengan-negara-lain?page=all, accessed on 14 May 2020). This denial response changed after entering the second phase with the emergence of the Delta variant in late 2021 (Mietzner 2023). The difference in the characteristics of the government’s response between the two phases emphasizes the significance of analyzing public trust in the initial phase of handling COVID-19, to understand if the online conversation map shows the public’s critical attitude towards the denial response demonstrated by the government during the early phase of the COVID-19 pandemic, particularly regarding restriction policy.
The implementation of the restriction policy is related to the state’s economic and political capacity (Croissant and Hellmann 2023). Economically, implementing the restriction policy has implications for the state’s ability to provide for the needs of society during restrictions, including ensuring that basic economic activities can continue. Politically, the imposition of restrictions is prone to triggering resistance, as has happened in several countries which imposed restrictions by making decisions in secret and implementing them in an authoritarian manner.
In the case of Indonesia, the discourse on imposing restrictions was initiated by community groups as a form of criticism of the government’s response at the beginning of the pandemic phase, which was denial and anti-science in nature. To explain this phenomenon, this article assumes that the government’s consistency determines public trust in it using its capacity to implement LSSR. The main argument is that the government’s past performance in maintaining previous policies (over a significant period) is essential in maintaining public trust (van Engen et al. 2019) and even more critical in facing the denial response indicated in the early phase of the pandemic handling in Indonesia.
This study builds an argument base on Croissant and Hellmann’s (Croissant and Hellmann 2023) conceptual framework regarding state capacity and public response to policies taken by the government. State capacity, typically defined as the ability of the state to achieve its objectives (Acemoglu and Robinson 2019), has been linked to numerous factors, including positive pandemic outcomes (Serikbayeva et al. 2021). However, this article focuses on the government’s consistency in using its capacity during a pandemic. This consistency will be reviewed from public online talks during the initial phase of handling COVID-19 in Indonesia, especially to see whether the denial and anti-science response the government initially showed has changed after the netizens encouraged the government to establish an LSSR policy.
To examine the argument, this article uses social network analysis to map the relation of LSSR issues with other topics of public concern, such as who is most associated by the public with this issue, and what the prevailing sentiment is. The analysis of maps of discussion and social networks that produced such meaning will show how the LSSR issue is politicized, in the sense of how its meaning is contested in a time of pandemic to build public trust.

2. Materials and Methods

This article considers text as a product representing power relations in Twitter discussions. It is crucial to identify the kind of text that appears in online discussions to identify the underlying power or interest that shaped the arguments behind such text. For this reason, this article uses a social network analysis approach that analyses big data of public discussions on implementing LSSR from Twitter API.
The data was acquired online through Twitter data mining using the Drone Emprit Analysis platform from 10 April 2020 to 10 May 2020. The keywords used are “Pembatasan Sosial Berskala Besar” (Large-Scale Social Restrictions) and “PSBB” (LSSR). Both terms are selected since they are the official names of government policies, and the selected tweets should come from Indonesia. This period was selected since 10 April 2020, was when LSSR was first implemented in Indonesia, which is in the Province of DKI Jakarta, the capital city of Indonesia (https://www.cnnindonesia.com/nasional/20200417074310-20-494387/daftar-daerah-yang-disetujui-dan-belum-boleh-terapkan-psbb, accessed on 14 May 2020).
Data collection shows that there are 222,736 tweets. From that aggregate, data processing was done through an application provided by the Drone Emprit Academic social media monitoring platform (academic.droneemprit.id). Data processing results from online discussion interaction imaging, sentiment analysis, and emotional analysis were used to analyze discussion characters concerning LSSR implementation. These data were then analyzed to explain how the public relates the LSSR implementation issue with other topics that took public attention. Social network analysis data processing was done with the same platform to identify actors associated with LSSR implementation issues and relations among said actors. The results of interpreting such data were analyzed to elaborate on the potentialities of politicizing the LSSR issue.

3. Results

The discussion trend regarding LSSR shows a high engagement from the public since the policy was first enacted in DKI Jakarta, the province with the highest number of positive COVID-19 cases in Indonesia. The following figure shows the engagement dynamics throughout data collection, covering interactions in mentions, retweets, and replies. The data shows that LSSR implementation is an issue that is regarded as necessary since there is daily information or mentions in regards to LSSR, as well as public response in the forms of retweets or hashtags that are related to LSSR. The tendency of response to come in the form of retweets to continue the messages shows that the messages contain essential meaning for the public or have informative value, so that there is relevance between the messages and public needs.
The trend in Figure 1 shows a fluctuating dynamic, with several high points recorded on 11 April 2020, 5 May 2020, and 8 May 2020.
Figure 2 shows that the trend in sentiment indicates an almost balanced response between positive (50 percent) and negative (44 percent) responses. The Figure 3 below shows that negative responses rose several times, exceeding positive and neutral responses, that is, on 13 April 2020 (6504 negative mentions), 28 April 2020 (7497 negative mentions), and 4 May 2020 (5708 negative mentions). Such statements with a negative tone contain the public’s criticism of the weakness of LSSR enforcement throughout the implementation of LSSR and doubts about the effectiveness of LSSR implementation.
The tendency of negative responses that continue to fill discussions on Twitter for a month since the enactment of LSSR is confirmed in the analysis of public emotion tendency reflected in posted tweets. Figure 4 shows the highest tendency in statements containing anticipatory messages (3017 mentions). Anticipatory messages contain statements on the government’s efforts in LSSR implementation or situation updates, which are mainly informative. Data also showed that statements that reflect trust and anger also rank high.
The following data processing was done to identify social networks within the dynamics of discussions on LSSR implementation. Based on the data above, several crucial momentums that mark specific responses were identified. This data was then cross-checked with actual dates connected to the implementation of LSSR. This policy was not enacted simultaneously in all regions in Indonesia but differs according to authorization messages from the Indonesian Ministry of Health. Momentum cross-checks from these online and real-life discussions were used to understand the context that made way for specific discussion dynamics, including the mobilization of social networks in such dynamics.
Social network analysis results first served as the social dynamics on 10 April 2020, the first day of LSSR implementation in Jakarta, the capital of Indonesia, and the region with the highest number of COVID-19 cases in Indonesia.
Figure 5 shows that all accounts responded positively to implementing LSSR in Jakarta (marked green in the social network analysis map). Three accounts stood out in the discussion dynamics. The accounts @CNNIndonesia and @DKIJakarta had close and even intersecting positions, ultimately indicating that both accounts were interrelated in providing information on LSSR. The account @CNNIndonesia is a media account, while @DKIJakarta is the official account of the DKI Jakarta Provincial Government. The interrelation between the two showed the role of information arbitrage taken up by media accounts in providing information from the government. In the lower-left section, there are other media under the account @nuicemedia, which despite its rather significant role, is separated from the others. This was caused by the fact that this account provided information in English, which reached out to a different audience than other accounts, which tended to gravitate towards the DKI Jakarta Government account.
The following social network analysis map is regarding 13 April 2020, marked by many tweets with negative sentiments. The negative sentiments that gained strength in Twitter discussions were triggered by tweets from the account @ainunnajib that contained criticism against the Health Minister who refused to give authorization for the Palangkaraya Municipal Government to enact LSSR, reasoning that COVID-19 had not reached a critical level in Palangkaraya, even though the purpose of LSSR is to control infection so that there would not be a critical level (https://twitter.com/ainunnajib/status/1249490191074471936, accessed on 18 May 2020). This tweet is coupled with the corresponding document from the Minister of Health. Since being posted at 07:30 a.m., this tweet garnered an increasing engagement which peaked at 11:59 a.m., as seen in the Figure 6.
Discussion surveillance data on 28 April 2020 captured heightened negative sentiments, which peaked at 10:59 a.m. The social network analysis mapping figure showed that on that day, at least three interconnected clusters voiced discussions with negative tones, with the account @rasjawa as the epicenter (Figure 7). Messages posted by this account were then voiced again by the accounts @fadlizon and @tempo.com. Only one account managed to create a cluster with a positive tone (@e100s), but other accounts did not echo it. The account @rasjawa posted narratives on his experience witnessing a man riding a motorbike with his child who was stopped by police for violating LSSR in Bandung (https://twitter.com/rasjawa/status/1254674390467268608, accessed on 19 May 2020). The implementation of LSSR in Bandung forbade motorcyclists to carry passengers, which led to the man’s child being ordered to get off the motorbike and switch to a means of public transport along with other passengers whom the child did not know. The account @rasjawa criticized Bandung LSSR regulations for being illogical. This statement garnered a significant response from the public, as seen in the following social network analysis mapping.
Statements with negative sentiments exceeded positive statements again on 4 May 2020. On this day, it was recorded that negative sentiments appeared more than 5710 times, slightly higher than positive sentiments with 4237 appearances. In the following social network analysis mapping (Figure 8), the positive sentiment cluster can be seen to be dominated by the account @ridwankamil, which stood at the center of the discussion, while other accounts which sent negative sentiments are spread across several clusters, among those which stood up was @wanderstruck and other accounts which were spread in the lower-right section.
These negative sentiments accounts did not show an interrelation with one another, indicating that their messages were different but contained negative sentiments equally. For example, the account @wanderstruck posted a message with information on the condition of Semarang Zoo, which had difficulties being in a Red Zone that implemented LSSR, resulting in difficulties for feeding the zoo animals after the closing of the zoo during LSSR (https://twitter.com/wanderstruck__/status/1257080327249342464, accessed on 19 May 2020). Several other accounts with negative tones contained other messages, such as criticism of political figures who used LSSR as a pretext to avoid investigations by the police. Overall, the messages with negative tones were not related to each other but garnered a high engagement which exceeded the number of positive sentiments whose contents were directly related to the implementation of LSSR.
The account @ridwankamil, which created a rather large cluster at the center of the discussion, posted a status that contained information on pickup services from the West Java government for West Java residents then waiting in Saudi Arabia. These West Java residents then underwent a period of isolation per COVID-19 health protocol (https://twitter.com/ridwankamil/status/1257207671981248513, accessed on 19 May 2020). The account of @ridwankamil is the personal account of the West Java governor, who is regularly active on Twitter, not only during the duration of the COVID-19 pandemic.
The social network analysis data provided in the Figure 8 above showed several findings that will be elaborated further in the following discussion section.

4. Discussion

This article seeks to discuss whether the dynamics of discussions on Twitter on LSSR implementation reflect public trust in implementing such a policy. By identifying momentum referent points that generated extremely negative responses, social network analysis data from the previous section showed several essential findings, which are:
First, social network analysis maps show that discussion clusters are sporadic, with no account dominating discussion topics. This indicated that discussion dynamics were not planned to be organized as a channel for delivering information or socialization on the details of LSSR policies. This is also supported by official government accounts that were not actively providing information. Several accounts related to governments and that played an active role were @jokowi, @ridwankamil, and @ganjarpranowo. The exception applied for DKI Jakarta, in which the account @DKIJakarta and the account @aniesbaswedan were both active in providing information on LSSR. Communication models through these personal accounts are effective enough to create closer relations between the public and their leader but risk being “attacked” by anonymous accounts that dislike the leader figure. This model also shows that during a pandemic, interpersonal information networks play a more significant part (Bennett and Segerberg 2012; Jang and Baek 2019). On the other hand, information distribution through interpersonal networks is vulnerable to misinformation and hoaxes, which are counterproductive to the government’s interest in building public trust through objective information on COVID-19. Online media accounts are also considered to play an active role in discussion engagement, especially in information arbitrage or connecting information from the government to the public.
Second, regional leaders’ accounts play a more active role in delivering information, as seen from the character of the messages, which tended to be anticipatory. Conversely, the accounts representing national figures or government institutions, though playing a role, more often rely on traditional media or online media as a channel to funnel information, as indicated by the mass media engagement model that played a part in information arbitrage. The local government played a more significant role in LSSR implementation since, technically, these policies were implemented by the local governments. Nevertheless, government messages seemed to lack coordination when addressing a complaint, or public reports on regulations between the implementation of LSSR in regions, or even differences of interpretation on LSSR implementation in inter-regional relations such as in transport matters. This became an issue because it created public confusion, which questions which message to trust, ultimately allowing the public to determine their attitudes even if they violate LSSR regulations (Limaye et al. 2020).
Third, official accounts from government institutions did not seem to be involved in the discussions, primarily when negative sentiments increased in numbers. No efforts were seen from the official government accounts to respond to the negative sentiments from statements containing criticism or public reports on LSSR violations. This is seen from social network analysis mapping that illustrates that negative clusters, large or small, did not interact with positive clusters. In a deeper analysis, the government did respond to critics, for example, to the messages from the account @rasjawa. However, the clarificatory response from the government on the reason for the prohibition of a motorcyclist from carrying passengers (though family members) did not invite engagements from other accounts that retweeted the clarificatory statement. This reinforces the assumption of a public legitimacy crisis on formal and authoritative sources of information (Eysenbach 2007; Limaye et al. 2020).
Fourth, negative sentiments arose out of ambiguity in implementing LSSR or for illogical regulations. The ambiguity in LSSR implementation is seen in examples such as critics of the government’s neglect of those who still gather in crowds, do not use masks, or violate other LSSR regulations. Additional examples criticized illogical regulations, for example, those aimed at implementing LSSR for motorcyclists who are barred from carrying passengers, including family members. Critics against the process of LSSR authorization by the Ministry of Health also arose as a form of doubting the government policies, exceptionally when the government did not authorize LSSR permissions. Such negative sentiments that were voiced in the form of critics did not show public rejection against LSSR implementation, but on the contrary, it showed public doubt in government consistency and assertiveness in implementing LSSR. The debate on a lockdown or regional quarantine, as pictured in the early stages of the discourse, did not continue when the government opted to implement LSSR. This indicates public support for the government policy, but the public’s critical stance will continue arising when the implementation of this policy is deemed inconsistent, lacking coordination, and lenient in punishing those who violate the policy. The pandemic situation on its own has brought about uncertainty, including the uncertainty of how long LSSR will last, so that in this situation the government needs to provide a guarantee to the public that each policy that is taken will lead the public out from the state of crisis (Chen et al. 2020).
Fifth, positive messages that invite many engagements have a particular character that could be reproduced and echoed on a larger scale to build public trust. Such a character is actionable information, which means that sent messages should be able to be used as a guide to anticipate situational developments so that the public can prepare themselves in the middle of uncertainty (Gerwin 2012). Dynamic analysis data from Twitter conversation dynamics confirmed this, mainly covering anticipatory measures (more than 3000 tweets). Messages with actionable information also include health recommendations, which are also required by the public to maintain their health (Murthy 2013), as well as opening space for the public to participate in self-regulating and limiting interaction with others as part of supporting LSSR implementation. Official government accounts, be that on the local or national level, including personal accounts of government leaders or regional leaders, need to provide more messages containing actionable information to direct public behavior in accordance to health protocols and LSSR regulations.

5. Conclusions

In building public trust in the government during a pandemic, social media conversation, including Twitter, holds strategic importance, for it can be used to provide information on the developments of pandemic handling so that the public can avoid being left in a state of uncertainty. Efforts to build trust relate to communicating risks to the public affected by implementing LSSR and controlling negative sentiments that arise responsively. Analysis of the social network analysis mapping results showed that the public holds LSSR-related information in high regard, which is marked by the high number of engagements in discussions on this issue. Nevertheless, such enthusiasm is not balanced by the government accounts’ capacity to manage communications. The solid interpersonal networks in information distribution reinforce such an assumption.
The affirmation will reflect public trust in disseminated information concerning LSSR. The high tendency of negative sentiments in LSSR-related discussions shows a low level of public legitimacy on informative messages sent by the government, since the public noticed a contradiction between LSSR regulations and their implementation. Such a level of negative sentiment is not due to the public’s rejection of LSSR, but to public doubt in the effectiveness of LSSR implementation. This public doubt can be managed through disseminating counter-information on the results of LSSR, such as providing data on cases during the implementation of LSSR. Public trust must be built through legitimacy born from a deliberation process with logical argumentation, not an affiliation to a particular figure.
During the pandemic, the government must promptly communicate the crisis effectively and efficiently to the public since failure will spread fear, anxiety, and uncertainty to the people. With the scale and reach of the pandemic, which is spreading rapidly, there is an urgent need to build communication practices to disseminate the latest accurate and timely information to respond to public aspiration. The government can partner with social media to identify, fact-check, and even delete false or expired information to optimize these social networks to support COVID-19 handling.
Even though online discussions can provide an overview of public trust or distrust in the government’s capacity to handle COVID-19, sentiment analysis from online discussions has limitations because the themes discussed are temporary and dynamic, resulting in the difficulty of building strong arguments as a basis for encouraging government policies that are more responsive in handling the pandemic. Therefore, to ensure the government’s consistency in using its capacity in situations of uncertainty, there need to be continuous efforts from the public to criticize the government’s performance by using online media and other representation institutions.

Funding

This research was funded by THE MINISTRY OF RESEARCH AND TECHNOLOGY/NATIONAL RESEARCH AND INNOVATION AGENCY, THE REPUBLIC OF INDONESIA, grant number 1827/UN6.3.1/LT/2020 and The APC was funded by the Directorate of Research and Community Engagement Universitas Padjadjaran.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Raw data and processing results are obtained through the Drone Emprit Analysis online platform (https://dea.uii.ac.id, accessed on 25 February 2023), which can be accessed on limited access (by a login account mechanism).

Acknowledgments

The author would like to thank the Ministry for providing the grant, Universitas Padjadjaran for supporting this research, and Drone Emprit Academic social media monitoring platform, facilitated by Universitas Islam Indonesia, Yogyakarta, for providing data crawling from API Twitter.

Conflicts of Interest

The author declares no conflict of interest.

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Figure 1. Dynamics of discussions on LSSR.
Figure 1. Dynamics of discussions on LSSR.
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Figure 2. Trends in discussions about LSSR.
Figure 2. Trends in discussions about LSSR.
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Figure 3. Trends on sentiments in discussions on LSSR.
Figure 3. Trends on sentiments in discussions on LSSR.
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Figure 4. Emotional analysis of discussions on LSSR.
Figure 4. Emotional analysis of discussions on LSSR.
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Figure 5. Social network analysis on the first day of LSSR on 10 April 2020; the condition was recorded at 11:59 p.m.
Figure 5. Social network analysis on the first day of LSSR on 10 April 2020; the condition was recorded at 11:59 p.m.
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Figure 6. Social Network Analysis on 13 April 2020; the condition was recorded at 11:59 a.m.
Figure 6. Social Network Analysis on 13 April 2020; the condition was recorded at 11:59 a.m.
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Figure 7. Social Network Analysis on 28 April 2020; the condition was recorded at 10:59 a.m.
Figure 7. Social Network Analysis on 28 April 2020; the condition was recorded at 10:59 a.m.
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Figure 8. Social Network Analysis on 4 May 2020; the condition was recorded at 11:59 p.m.
Figure 8. Social Network Analysis on 4 May 2020; the condition was recorded at 11:59 p.m.
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Paskarina, C. Public Trust in the Time of Pandemic: An Analysis of Social Networks in the Discourse of Large-Scale Social Restrictions in Indonesia. Soc. Sci. 2023, 12, 186. https://doi.org/10.3390/socsci12030186

AMA Style

Paskarina C. Public Trust in the Time of Pandemic: An Analysis of Social Networks in the Discourse of Large-Scale Social Restrictions in Indonesia. Social Sciences. 2023; 12(3):186. https://doi.org/10.3390/socsci12030186

Chicago/Turabian Style

Paskarina, Caroline. 2023. "Public Trust in the Time of Pandemic: An Analysis of Social Networks in the Discourse of Large-Scale Social Restrictions in Indonesia" Social Sciences 12, no. 3: 186. https://doi.org/10.3390/socsci12030186

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