• Asian Journal for Public Opinion Research
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• v.5 no.4
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• pp.285-301
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• 2018

There have been many studies that applied a data-driven analysis method to social media data, and some have even argued that this method can replace traditional polls. However, some other studies show contradictory results. There seems to be no consensus as to the methodology of data collection and analysis. But as social media-based election research continues and the data collection and analysis methodology keep developing, we need to review the key points of the controversy and to identify ways to go forward. Although some previous studies have reviewed the strengths and weaknesses of the social media-based election studies, they focused on predictive performance and did not adequately address other studies that utilized social media to address other issues related with public opinion during elections, such as public agenda or information diffusion. This paper tries to find out what information we can get by utilizing social media data and what limitations social media data has. Also, we review the various attempts to overcome these limitations. Finally, we suggest how we can best utilize social media data in understanding public opinion during elections.

• Asian Journal for Public Opinion Research
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• v.8 no.1
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• pp.41-58
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• 2020

This article attempts to explain social media use within the relationship between the public and government of Indonesia in the era of digital government, as well as to consider public opinion on this matter. This research is based on the application of social media logic and the theory of dialogic communication and action. A qualitative descriptive approach was used to observe the general behavior of social media use by 34 ministries in Indonesia, including interviews with the resource persons within the ministries and focus group discussions with members of the public and observers. The research shows that the relationship between the public and government is accommodative and in line with social media logic. The public sector implemented social media as its platform, which has been further adopted by all ministries. The public sector cannot avoid social media, as it has become part of basic connectivity, even though the use of social media by the government still tends to be in the form of presenting public information. There are advantages and disadvantages of the usage of social media by the government. The advantages include allowing the government to be more open via social media so that communication between the government as the ruling organization and its public can be more fluent. Social media provides space to the public sector in the practice of digital government. Some disadvantages arise as logical consequences that usage of social media cannot be separated from the implementation of digital government. The adaptive behavior of social media by the government can be found by following social media logic as part of digital government implementation. Social media logic causes the government to follow the rules of social media. In this context, the strength and power of the country seems to be regulated by social media. Therefore, more studies on how social media is managed in the context of its usage as digital government support is needed.

• Asian Journal for Public Opinion Research
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• v.8 no.3
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• pp.393-406
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• 2020

The discourse on the lockdown in Indonesia is getting stronger due to the increasing number of positive cases of the coronavirus and the death rate. As of August 12, 2020, the confirmed number of COVID-19 cases in Indonesia reached 130,718. There were 85,798 victims who have recovered and 5,903 who have died. Data show a significant increase in cases of COVID-19 every day. For this reason, there needs to be an evaluation of the government policy of the Republic of Indonesia in dealing with the COVID-19 pandemic in Indonesia. An evaluation of policies for handling the pandemic must include public opinion to determine any weaknesses of this policy. The development of public opinion about the lockdown policy can be understood through social media. During the COVID-19 pandemic, measuring public opinion through traditional methods (surveys) was difficult. For this reason, we utilized big data on social media as research data. The main purpose of this study is to understand public opinion on the lockdown policy in overcoming the COVID-19 pandemic in Indonesia. The things observed included: volume of Twitter users, top influencers, top tweets, and communication networks between Twitter users. For the methodological development of future public opinion research, the researchers outline the obstacles faced in researching public opinion based on big data from Twitter. The research results show that the lockdown policy is an interesting issue, as evidenced by the number of active users (79,502) forming 133,209 networks. Posts about the lockdown on Twitter continued to increase after the implementation of the lockdown policy on April 10, 2020. The lockdown policy has caused various reactions, seen from the word analysis showing 14.8% positive sentiment, 17.5% negative, and 67.67% non-categorized words. Sources of information who have played the roles of top influencers regarding the lockdown policy include: Jokowi (the president of the Republic of Indonesia), online media, television media, government departments, and governors. Based on the analysis of the network structure, it shows that Jokowi has a central role in controlling the lockdown policy. Several challenges were found in this study: 1) choosing keywords for downloading data, 2) categorizing words containing public opinion sentiment, and 3) determining the sample size.

• Journal of Internet Computing and Services
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• v.19 no.4
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• pp.53-63
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• 2018

The traditional mass media function of conveying information and forming public opinion has rapidly changed into an environment in which information and opinions are shared through social media with the development of ICT technology, and such social media further strengthens its influence. In other words, it has been confirmed that the influence of the public opinion through the production and sharing of public opinion on political, social and economic changes is increasing, and this change is already in use on the political campaign. In addition, efforts to grasp and reflect the opinions of the public by utilizing social media are being actively carried out not only in the political area but also in the public area. The purpose of this study is to explore the possibility of using social media based public opinion in educational policy. We collected media data, analyzed the main topic and probability of occurrence of each topic, and topic trends. As a result, we were able to catch the main interest of the public(the 'Domestic Computer Education Time' accounted for 43.99%, and 'Prime Project Selection' topics was 36.81% and 'Artificial Intelligence Program' topics was 7.94%). In addition, we could get a suggestion that flexible policies should be established according to the timing of the curriculum and the subject of the policy even if the category of the policy is same.

• Asian Journal for Public Opinion Research
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• v.1 no.3
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• pp.217-231
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• 2014

This study begins with a review of commonly discussed dimensions of public risk perception that may influence public opinion toward risks. Factors that have been revealed by the literature to have substantial impact on risk perception, such as demographic background, trust, and media environment, are also discussed. Meanwhile, we evaluate two well-known research models in the realm of risk analysis: 1) the psychometric paradigm, and 2) the social amplification of risk framework (SARF). Based on a literature review, this study suggests that, besides the psychological and social approach, models of risk perception and risk communication research should shift to a more comprehensive one by considering the interrelations between laypeople and the environment. This study proposes a research model from the perspective of social cognitive theory (SCT) as a potential framework for future studies: 1) in the societal environment, individuals' risk perception and information seeking behavior, which is determined by risk perception will be influenced by trust in regulators and interpersonal trust; 2) in the media environment, individuals' risk perception and information seeking behavior will be influenced by individuals' perceived information characteristics. Knowledge about risk accumulated through information seeking will change risk perception in a longitudinal process.

• Asian Journal for Public Opinion Research
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• v.9 no.3
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• pp.240-265
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• 2021

Public services need to be evaluated regularly to identify areas that need further improvement. Data collection via Twitter is affordable and timely, so it has the potential to be utilized to evaluate the quality of public service. This study utilizes tweets mentioning three service units of the provincial government of Jakarta and applies both sentiment analysis and topic classification to predict a rating/score of public service quality. The research goal is to examine if the evaluation of public services based on social media data is possible. The findings indicate that the use of Twitter has an advantage in terms of sample size and variety of opinions. Tweets can be translated into scores as well. Nonetheless, the representativeness issue and the predominance of complaint tweets can affect the reliability of the results.

• The Journal of the Convergence on Culture Technology
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• v.6 no.1
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• pp.111-120
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• 2020

As an application of big data and artificial intelligence techniques, this study proposes an atypical language-based sentimental opinion poll methodology, unlike conventional opinion poll methodology. An alternative method for the sentimental classification model based on existing statistical analysis was to collect real-time Twitter data related to parliamentary elections and perform empirical analyses on the Polarity and Intensity of public opinion using attribute-based sensitivity analysis. In order to classify the polarity of words used on individual SNS, the polarity of the new Twitter data was estimated using the learned Lasso and Ridge regression models while extracting independent variables that greatly affect the polarity variables. A social network analysis of the relationships of people with friends on SNS suggested a way to identify peer group sensitivity. Based on what voters expressed on social media, political opinion sensitivity analysis was used to predict party approval rating and measure the accuracy of the predictive model polarity analysis, confirming the applicability of the sensitivity analysis methodology in the political field.

• Asian Journal for Public Opinion Research
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• v.10 no.1
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• pp.51-73
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• 2022

This study investigated 3.50 million Facebook reactions collected from 9,429 Bangladeshi news items about rape shared on social media from 2016 to 2021. The primary aim of this study was to understand users' different reaction patterns based on the five major Facebook reactions (i.e., love, haha, wow, sad, and angry). Based on the theories of emotion, we quantitatively answer one research question: How do social media users react to rape with the five major Facebook reactions? The results suggest that users are more likely to express disdain toward rape and sympathy toward the victims using Facebook reactions by using the angry button, along with the sad button. In rape news, both reactions are consistent and maintain a strong positive correlation, meaning they increase and decrease together. Although many users tend to mock and laugh at rape incidents and the victims, trend lines suggest that such expressions may not be consistent with time. Despite contextual relevance, we presume that in socially and morally unacceptable events like rape and war, the valences of reactions alter to some extent: angry and sad usually become positive, while love, wow, and haha become negative. Some strengths and limitations of the study are discussed as well.

• Asian Journal for Public Opinion Research
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• v.10 no.3
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• pp.230-253
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• 2022

Based on Goffman's dramaturgical theory and self-objectification framework, this study examined: 1) Chinese female's WeChat self-presentation, 2) the impact of WeChat usage on female self-objectification, and 3) the impact of self-objectification on WeChat self-presentation tactics. An online survey was conducted. The main findings include: 1) most of the participants chose to beautify their pictures and videos before they posted them, 2) the respondents attached higher importance to appearance-based body attributes than competence-based ones, 3) the most frequently applied self-presentation tactic was ingratiation, 4) WeChat usage was not a predictor of Chinese women's self-objectification, and, 5) along with extroversion, self-objectification had an impact on ingratiation, supplication, self-promotion, and exemplification. Meanwhile, use of the electronic curtain and audience sifting to control who can see a post and for how long demonstrated the empowerment of the users when they conduct self-presentation.

• Asian Journal for Public Opinion Research
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• v.1 no.1
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• pp.42-60
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• 2013

This article introduces the infrastructure of public opinion research in Japan by reviewing the development of polling organizations and the current situation of social surveys. In Japan, the polling infrastructure developed through the direction and encouragement of the U.S. occupation authorities. In the early 1969s, however, survey researchers began to conduct their own original polls in not only domestic but also cross-national contexts. An exploration of recent survey trends reveals that polling organizations tended to conduct more surveys during summer, in the mid-range of sample size (1,000-2,999), based on random sampling (response rates of 40-50%), and through the mail between April 2011 and March 2012. The media was the most active polling sector.