Twitter Based Digital Social Movement Pattern to Fight COVID-19

Twitter has become a tool for people to trigger a social change, like what is happening right now during COVID-19 outbreaks. Most people are using social media platforms to express their perspectives. For the first time, this research aimed to analyze the pattern of a social movement that happened during COVID-19 Outbreaks by analyzing the Twitter dataset contains 23,476 tweets worldwide with the #COVID19 hashtag which was obtained from 02 March to 09 April 2020. Social Network Analysis tools are used to understand the pattern of movement. This research concluded that if the Government and Mainstream Media Twitter account triggered the conversation in the social media platform, followed by the activists and celebrities who engage in conversation between their followers, an ordinary person spread the point of view of the Government and Mainstream Media across their conversation network. The COVID-19 hashtag successfully engaged 10 protest clusters, which pushed the people to fight against COVID-19 in their countries, mostly targeting the government-related account. The digital social movement pattern is relatively different from the traditional social movement, even it has the same steps, which emerge, coalesce, bureaucratise, and the movement itself, but it takes place in the Digital Public Sphere without any social or political boundaries. The digital social movement forced the government to implement a better policy to fight the COVID-19 Pandemic, including to close the national border to prevent unnecessary effects of International Migration.

Shifting the Blame: Storm and Wildfire Dramatic Images in American News Media

Some media frames might be likely to seek to evoke a certain sentiment, and that natural disaster coverage by the media focuses on the current impact of disasters. In their coverage, American news media use polar sentiment words to create bleeding images of natural disasters, potentially counter-productive to the wisdom of dealing with the natural disaster. Identifying the sentiment words that lead to a misperception of natural disasters can help journalists adopt the wisdom that natural disasters are not a human enemy. The corpus-assisted discourse studies (CADS) reported in this article investigates the American media's issues for dramatic reporting and the polar sentiment words utilized in the framing. The corpus is built from 100 news articles reporting wildfires and storms by ten major online American news media published from January 1, 2018, through December 31, 2020. It uses AntConc to generate word-list and word-link from which it identifies the dominant issues. Subsequently, it compares the AntConc word-list with A List of Sentiment Words to reveal the tones and dramatic imaging. The findings show that the dominant issues in storm reporting are description, impact, and prediction, while wildfire reporting are cause, impact, action, and prediction. The negative polar words produce dramatic images of storm as a violent beast and wildfire as a vengeful invader. Such description is provocative to blaming natural disasters as a cause of human suffering rather than improving our behaviors to reduce the suffering. Thus, it is counter-productive to acquiring wisdom for dealing with natural disasters.

The Unemployment Rate Amid the COVID-19 Pandemic: Propose the Best Practices Policy to Maintain Labor Market Stability

This study analyzes the impact of the shocks caused by the COVID-19 pandemic on the labor market. The research is vital for expanding the literature about maintaining the unemployment rate amid crisis, ultimately reducing unnecessary social costs. The quantitative approach in this study uses a Granger causality test to understand the effect of the shock caused by the COVID-19 pandemic on unemployment. Meanwhile, the qualitative approach in this study uses literature related to economic growth, crisis management, and unemployment. Granger causality tests show that economic slowdown hurts the unemployment rate. Based on discussion and synthesis from works of literature, this paper recommends some of the policies to maintain growth and prevent a more severe collapse in the labor market; the government needs to sustain aggregate demand and supply. Also, ensure the supply chain runs well amid various restrictions. Besides, this paper also proposes that the government maximizes alternative budget resources. Meanwhile, strengthening the labor system and developing health and food security industries must be a priority policy amid-post the pandemic.

Analysis of the E-Government Initiative at Local Government Level in Bandung City, Indonesia

This research aims to analyze aspects affecting the implementation of electronic parking, a digital- based public services provision in parking. The concept of digital divide, workforce, regulation, and infrastructure were used to conduct the analysis. This study employed a qualitative research methodology with qualitative data collection techniques through interviews with two officers of the Parking Technical Implementation Unit (TIU) - the Department of Transportation Bandung City Government, 4 parking attendants, and 100 people as the roadside parking users. To enrich the data, observation and study documents were also conducted. The research used a descriptive analysis combined with simple descriptive quantitative data. It is evident from this study that four primary aspects hindered the implementation of the electronic-parking initiative. Those aspects are a large gap in the digital divide, low workforce quality and quantity, the absence of the proper regulations, and futile infrastructure. Adding to these four barriers, we also found other significant aspects: the investment that has not been strategically designed, the lack of leadership, and the low quality of education and marketing. All these three additional aspects also contribute to the failure in meeting the objective of the electronic parking initiative. This finding suggests that any new initiatives in public service provision, mainly using ICT, need to be well communicated and consulted with the implementing units. Furthermore, the initiative needs to be complemented with an acceptable set of policies to ensure its sustainability.

Pilkada Amidst a Pandemic: The Role of The Electronic Word of Mouth in Political Brand and Voting Intention

The Regional Head Election campaign frequently uses electronic Word of Mouth (eWOM) communication because of social media's growth and the Covid-19 pandemic that took place during the election year. In commercial brands, eWOM impact has influence brand equity and purchase decisions. However, in political brands, this has not been proven. Therefore, by using the regional head candidate of Purbalingga Regency as a political brand, this study examines the effect of eWOM on developing candidate brand equity and relates it to voting intention. Brand equity using a brand pyramid model with brand equity forming variables consisting of a candidate brand awareness, a candidate brand performance-imagery, a candidate brand judgment-feelings, and a candidate brand resonance. The study involved 260 respondents who are people of Purbalingga Regency who may vote and use social media. The sampling method used was purposive sampling by conducting direct interviews with respondents. Data were analyzed using Structural Equation Model Partial Least Square (SEM PLS) analysis. The results showed that electronic Word of Mouth has a positive and significant effect on brand equity development variables. Developing brand equity affects the voting intention on candidate brand awareness and candidate brand resonance. The Result of this study found electronic Word of Mouth to have no direct influence on voting intention.

Utilization of Big Data Analysis Through Public Video, Virus Data Cooperation, and Social Media as the Surveillance to COVID-19 in Indonesia

This article discusses Big Data's use as a surveillance tool for the spread of Corona Virus Disease 2019 (COVID-19), both in Indonesia and the world. In Indonesia, the range of COVID-19 is increasingly sporadic, causing mass panic and Indonesia's geographical characteristics, which will be difficult when this spread could not control quickly. Researchers are conducting several studies to overcome this pandemic, including supervision, features, handling, mobility, patient interaction, treatment evaluation, and the biological structure. These studies become data and lead to Big Data. This article explores how to use Big Data analysis to monitor the spread of COVID-19 as a communication process that reflects mediated communication as a form of mobility and spatial relationships in communication practices. The method used in this article is a literature review and uses meta-synthesis techniques as its analysis. The literature sources used are articles in highly reputable international journals. Based on the reports, various ways to monitor the virus's spread, through public video data, GPS, and social media tracking, trace the patient's movement. Big Data can also provide data collaboration for viruses and pathogens for further research as digital mediated communication is anchored by the diversity of places and the mobility of people, data, and objects.

Content Analysis of Social Media: Public and Government Response to COVID-19 Pandemic in Indonesia

Nowadays, the use of social media to analyze disaster responses has become important. However, its application to support decision-making by the Government during disasters still present significant challenges. This article offers a complete analysis of the response of the public and the Government in dealing with the COVID-19 Pandemics in Indonesia. The content analysis uses to analyze the tweet post on Twitter to determine the public and government response. Data was collected from public and government tweets on Twitter and producing 11,578 community tweets from the public and 958 tweets from the government account. This data was collected from 2nd March until 15th April 2020. Public comments are sorted into six categories of comments, that is fate, logic, government mention, worry, scientist, and impression, while sentiments are classified as positive, negative, and neutral. Government comments are sorted into eight categories, namely information, education, operating, warnings, resources provision, volunteer recruitment, and rumors management. The results showed that the public encourages and supports the Government to cope with a pandemic think rationally and logically in dealing with this Pandemic. In addition, the study indicates that the Government has not used social media as a medium for communicating with the public. The quality of government response is not good, especially in the categories of information on operations, warnings, resources provision, recruitment of volunteers, and rumors management. The implication of this study suggests how the data might be useful for the Government in delivering information during the Pandemic.