Public Opinion Research Articles

Penerapan Teknologi Biopori Sebagai Upaya Mengurangi Genangan Air di Dusun Baroeh Gampong Jantho Aceh Besar

Gampong Jantho is one of the villages that has frequent waterlogging problems. The village is located below a hill range. The southern area of the village, named Dusun Baroeh, is lower than other ones. Additionally, Dusun Baroeh is also isolated from waterways by a road made of concrete and pavement. When rain occurs, Dusun Baroeh always faces waterlogging. Rainwater seepage also transports organic waste and deposits, together with waterlogging. Therefore, one effort to overcome this problem is to create a biopore infiltration hole by utilizing a polymer pipe and organic waste. The implementation of this technology results from a problem-solving perspective through the public opinion pull of villagers, field observations, problem formulation, planning of appropriate technology, and the implementation of biopores. The biopore infiltration holes were placed in six different sites that have frequent waterlogging: three sites in the residents' yards, one site on the footpath, and two sites in the residents' gardens. These biopores work by opening and expanding the water flow from stagnant surfaces to porous soil. This technology is expected to accelerate water infiltration, improve groundwater quality, and reduce stagnant water, which can spread disease.

"Do not inject our babies": a social listening analysis of public opinion about authorizing pediatric COVID-19 vaccines.

Designing effective childhood vaccination counseling guidelines, public health campaigns, and school-entry mandates requires a nuanced understanding of the information ecology in which parents make vaccination decisions. However, evidence is lacking on how best to "catch the signal" about the public's attitudes, beliefs, and misperceptions. In this study, we characterize public sentiment and discourse about vaccinating children against SARS-CoV-2 with mRNA vaccines to identify prevalent concerns about the vaccine and to understand anti-vaccine rhetorical strategies. We applied computational topic modeling to 149 897 comments submitted to regulations.gov in October 2021 and February 2022 regarding the Food and Drug Administration's Vaccines and Related Biological Products Advisory Committee's emergency use authorization of the COVID-19 vaccines for children. We used a latent Dirichlet allocation topic modeling algorithm to generate topics and then used iterative thematic and discursive analysis to identify relevant domains, themes, and rhetorical strategies. Three domains emerged: (1) specific concerns about the COVID-19 vaccines; (2) foundational beliefs shaping vaccine attitudes; and (3) rhetorical strategies deployed in anti-vaccine arguments. Computational social listening approaches can contribute to misinformation surveillance and evidence-based guidelines for vaccine counseling and public health promotion campaigns.

Impact of the 2022 energy crisis on energy transition awareness in Latvia

Citizens, businesses, and governments faced energy scarcity, skyrocketing costs, and a high degree of unpredictability due to the Russian invasion of Ukraine in 2022. This situation has forced the European Union and national governments to switch to local energy resources and increase energy efficiency more strictly. But has society's attitude changed in the same way? Two separate public opinion surveys and network analyses were carried out to gain an understanding of energy efficiency practices prevalent in Latvia before and after the war erupted. In addition, the energy community simulation tool has been used to quantify the economic indicators under various conditions.The household survey results show that there, in fact, have been relatively few measures adopted to increase energy efficiency among the population during the energy crisis. The developed policy energy community simulation tool shows, that the energy costs in existing multi-family buildings have increased from around 61 EUR/m2 to 83.5 EUR/m2. However, it is still not motivating households to seek solutions toward more efficient energy use and RES generation due to the governmental subsidies to cover steep cost increases. Interventions targeting efficient energy communities through building managers would give higher strength and long-term effects.

Whoosh User Sentiment Analysis on Social Media Using Word2Vec and the Best Naïve Bayes Probability Model

By using the Twitter microblogging feature, users can post short tweets with limited characters that express their thoughts and opinions regarding a matter. The newest transportation in Indonesia, a high-speed train namely Whoosh is one of the things that Twitter users responded to. This latest transportation has led to the emergence of opinions from the Indonesian people which are shared publicly in various media, one of which is social media. Therefore, to make it easier for business people or companies to understand public opinion regarding service improvements in the future, sentiment analysis on social media is needed to determine user opinions regarding high-speed train transportation. In this research, sentiment analysis of high-speed train users will be carried out on social media Twitter using Word2Vec and Naïve Bayes as classification methods. In this research, a comparison of Naïve Bayes models will also be carried out to find out the best Naïve Bayes method opportunity model. Simultaneously, the Word2vec feature extraction method was chosen because Word2Vec can be used to improve model performance and increase the accuracy of sentiment classification. This research found that the Word2Vec Skip-Gram model outperformed the Word2Vec CBOW model. The best model obtained was the use of the Gaussian Naïve Bayes and Word2Vec Skip-Gram models with an accuracy score of 77.18%, precision 70.35%, recall 76.09%, and f1-score 73.10%.

"Do not inject our babies": a social listening analysis of public opinion about authorizing pediatric COVID-19 vaccines.

Designing effective childhood vaccination counseling guidelines, public health campaigns, and school-entry mandates requires a nuanced understanding of the information ecology in which parents make vaccination decisions. However, evidence is lacking on how best to "catch the signal" about the public's attitudes, beliefs, and misperceptions. In this study, we characterize public sentiment and discourse about vaccinating children against SARS-CoV-2 with mRNA vaccines to identify prevalent concerns about the vaccine and to understand anti-vaccine rhetorical strategies. We applied computational topic modeling to 149 897 comments submitted to regulations.gov in October 2021 and February 2022 regarding the Food and Drug Administration's Vaccines and Related Biological Products Advisory Committee's emergency use authorization of the COVID-19 vaccines for children. We used a latent Dirichlet allocation topic modeling algorithm to generate topics and then used iterative thematic and discursive analysis to identify relevant domains, themes, and rhetorical strategies. Three domains emerged: (1) specific concerns about the COVID-19 vaccines; (2) foundational beliefs shaping vaccine attitudes; and (3) rhetorical strategies deployed in anti-vaccine arguments. Computational social listening approaches can contribute to misinformation surveillance and evidence-based guidelines for vaccine counseling and public health promotion campaigns.

ANALYZING IMRAN KHAN’S POST-PREMIERSHIP SPEECHES: A CRITICAL DISCOURSE PERSPECTIVE

The primary objective of this study is to explore the speeches made by well-known political figure in Pakistan, Mr. Imran Khan, following his removal on April 10, 2022. The research explores the persuasiveness of Khan's speeches, spurred on by his considerable influence, especially among young people. The context of Fairclough's 3D model was used to analyze five carefully selected speeches that were given between June 19, 2022, and March 25, 2023. After being translated from Urdu into English, the speeches were examined. Using the 3D model required close examination of the discourse practices, text, and sociocultural background in order to reveal the complex relationships between language, power, and sociopolitical setting in Pakistan. The analysis shows how skillfully Khan uses rhetorical elements like irony, satire, and intertextuality to address important topics, advocate for change, and raise social consciousness. These findings shed light on wider issues of public opinion, government, and social standards in addition to helping to comprehend Khan's communication tactics. This research sets the stage for future discussions on discourse analysis, political communication dynamics, and the role of language in shaping political discourse, ultimately enhancing our understanding of modern political dialogue in Pakistan.

The influence of 'Golden Age' authors of detective fiction, in particular, D. L. Sayers, on the public opinion of dentists and dentistry.

With her wide readership and sympathetic and intelligent handling of dentists and dentistry in her detective novels and short stories, it is probable that Dorothy Leigh Sayers(1893-1957) influenced the public perception of dentists favourably, as being true professionals, particularly after the 1921 Act made it a fully closed specialty. Her encounter with a dental automaton seen when she was very young is acknowledged by her as a formative influence.

Challenging POPular opinion: Porous organic polymers for atmospheric water harvesting

As humanity faces growing water scarcity in many parts of the world, innovative solutions are imperative to achieve equitable access to safe drinking water for all. Atmospheric water harvesting (AWH) is a highly promising solution to water scarcity, comprising water adsorption directly from air using hydrophilic adsorbents, followed by collection upon desorption. Porous organic polymers exhibit distinct advantages for AWH, including broad tailorability, desirable porous properties, and outstanding chemical and thermal stability. This perspective outlines the current state-of-the-art in porous organic materials for AWH, distinguishing between reticular and amorphous materials, to discern key properties and outline future design principles. We also outline key performance metrics and provide a guide for the characterisation of such porous organic materials for those seeking to enter the field of AWH.

법학 연구 방법 이대로 좋은가?

Law is one of the social sciences and a field that citizens most frequently encounter in their daily lives. Despite this, legal research methods are primarily limited to literature reviews, and it is challenging to find quantitative research methods such as surveys that meticulously capture and reflect the thoughts, opinions, and intentions of the public. Legal scholars may believe that their thoughts and opinions sufficiently represent those of the public, but this can be considered intellectual arrogance. Since the overall thoughts and opinions of the public are constantly changing, laws must be created or interpreted based on frequent and comprehensive understanding of these changes. Only then will the public accept and respect the law. Of course, introducing surveys as a legal research method does not mean that all legal issues can be resolved solely based on survey results. Adjustments must be made considering the specialized theories of law and fairness with other issues. However, the current research methods that do not reflect the public's opinions at all must be improved. For this to happen, scholars and practitioners of law need to explain legal terms in simple and clear language so that the general public can understand them. Then, they should ask the public for their opinions on these explanations. Additionally, law must be approached and understood as a field accessible to everyone. The current research methods, which make law seem inaccessible to the general public through complex and difficult terminology and explanations, are both arrogant and inefficient. Legal research methods need to become more democratic and open. The public should be able to think and deliberate on legal issues so that the law can be democratic, reasonable, and truly authoritative. This way, the law can become more approachable, gaining trust and acceptance from the public. Moreover, the introduction of surveys in legal research goes beyond merely collecting public opinions; it can serve as a crucial means of developing law as a ‘science.’ Surveys systematically collect and analyze the opinions and experiences of various social groups, providing empirical evidence for legal research. This significantly contributes to enhancing the validity and acceptability of the law. Quantitative data obtained through surveys play a critical role in analyzing the correlations and causalities between social phenomena. These data, combined with advanced statistical techniques, can offer precise interpretations of social phenomena. For example, statistically analyzing the impact of a specific law after its enactment can evaluate the law's effectiveness. This approach goes beyond mere textual or theoretical analysis, enabling a concrete understanding of the law's role and impact through actual social outcomes. Even though law has normative characteristics, these norms must be based on reality, requiring the reflection of the public's actual thoughts and behaviors. Surveys allow legal scholars to verify abstract theories within concrete and realistic contexts. By collecting and analyzing diverse public opinions, legal research can yield more objective and reliable results. This process aids in making more reasonable and fair decisions during the enactment, amendment, interpretation, and application of laws. For instance, by investigating public perceptions of actions on the boundary between crime and non-crime, the alignment of legal norms with reality can be evaluated. Additionally, surveys are essential for understanding the various issues addressed by law within social and cultural contexts. By systematically collecting and analyzing public opinions, legal research can adopt a more comprehensive and multifaceted perspective. This enables the law to respond more sensitively to social changes and demands, enhancing its legitimacy and effectiveness. Consequently, surveys can play a vital role in developing law into a more scientific disci

Social Media in Shaping Public Opinion Roles and Impact: A Systematic Review

This systematic literature review examines the impact of social media on public opinion and its implications for policy-making. Utilising the PRISMA framework, the study analysed 19 articles from Scopus and Web of Science databases published between 2013-2023. The review identified five main categories of social media platforms discussed; Twitter/X, Meta (Facebook, Instagram, WhatsApp), YouTube, Chinese apps (Sina Weibo, WeChat, QQ), and several unspecified platforms. Key themes emerged across these categories, including the role of social media in knowledge dissemination, creation of filter bubbles and echo chambers, amplification of diverse voices, and spread of misinformation. The findings highlighted social media potential for real-time public opinion monitoring, facilitating engagement between policymakers and citizens, and early identification of emerging issues. However, challenges such as information credibility and algorithmic curation of content were also noted. The review suggests that strategic use of social media can raise awareness and mobilise support for global initiatives like the Sustainable Development Goals. It emphasises the need for policymakers to understand and leverage social media's influence on public sentiment while addressing associated risks. The study contributes to a nuanced understanding of how different social media platforms shape public discourse and influence policy decisions in the digital age. Future research directions are proposed to further explore the complex dynamics between social media, public opinion, and governance in an evolving technological landscape. Keywords: Social media impact, public opinion formation, digital policymaking, online political discourse, civic engagement.

Naive Bayes Algorithm with Feature Selection Using Particle Swarm Optimization

The COVID-19 vaccine in Indonesia has led to the emergence of public opinion which is conveyed on social media such as Twitter. One of the analyses that can be done to produce various information from public opinion is sentiment analysis. Sentiment analysis is used to determine whether an opinion tends to be positive or negative. This study aims to classify the public opinion of the COVID-19 vaccine in Indonesia with sentiment analysis and to visualize the location of the sentiment of the COVID-19 vaccine tweet data in Indonesia. To achieve this aim, the Naïve Bayes algorithm with Particle Swarm Optimization (PSO) feature selection was used. This study uses opinions into positive and negative class sentiments towards 2,547 tweets related to the COVID-19 vaccine in Indonesia from January to June 2021. The results show that the distribution of positive and negative class sentiments is 2,328 and 219, respectively. In addition, the positive sentiment for the COVID-19 vaccine was dominated by people on the island of Java based on a random number matrix initialized by the PSO method. The classification of public opinion on Twitter media provides accurate and optimal performance results using a combination of the Naïve Bayes algorithm with PSO feature selection. The results of the combination of these methods have accuracy and F1 score values of 91.28% and 95.38%, respectively. The visualization of geo-spatial mapping showed that positive sentiments related to the COVID-19 vaccine exist in almost all regions in Indonesia but are dominated by the Jabodetabek area.

Public Opinion Towards Teenagers and Their Stress in Modern Era

Stress is the way the body reacts. It's an unavoidable consequence of life. Teen stress may be a big issue in today's society. Recent studies have shown that teens may develop more stress when compared to the adults. People don't remember those problems because they need to forget them. Stress may be a significant problem for teens. There are many factors that lead into teen stress, like school, drugs, peer pressure etc. Stress is the way the most of the humans react both physically and mentally affected due to the situations, changes and events in their lives. It is associated with the feeling of physical or emotional tension and accompanied by psychological process. It is based on the perception of the situation or circumstances. Stress issues are basic with numerous individuals announcing encountering extraordinary degrees of negative stress. Stress is a response to a changing, requesting condition. Appropriately considered, stress is extremely more about our ability to deal with change than it is about whether that change causes us to feel positive or negative. So here we are going to discover procedures that can help you securely and adequately decrease your weakness to encountering extreme negative pressure. Stress is a response to a changing, requesting condition. Appropriately considered, stress is extremely more about our ability to deal with change than it is about whether that change causes us to feel positive or negative. The research method followed here is the empirical research. A total of 200 samples have been taken out of which is taken through a convenient sampling method. The sample frame taken by the researcher is through online mode. The independent variable taken here is age, education, occupation, gender, marital status. The dependent variables are the causes that leads to teenage stress, the personal methods to relieve your stress and frequency of feeling stressed

Public Opinion and Reaction to Israel’s War on Gaza after October 7 in Türkiye

Public Opinion and Reaction to Israel’s War on Gaza after October 7 in Türkiye

STATE SUPPORT OF BUSINESS IN UKRAINE

The article highlights the main directions of state support for small and medium-sized businesses and the functions of the state as a supporter of entrepreneurship development, which consist in providing not only financial, but also informational support, creating and maintaining institutional support and infrastructure. The purpose of the article is to review and analyze the instruments of state regulation and support of entrepreneurship in the countries of the world and the measures and programs introduced by the Government of Ukraine to support and stimulate domestic business. Analysis, synthesis and modeling methods were used to study the state of research. The results of our research was carried out with the help of empirical methods: pedagogical observation, questionnaires, interviews, testing, the method of experimental evaluations. Mathematical statistics methods were used to process the research results. The reasons for the inefficient activity of enterprises are considered, which are connected, among other things, with an unbalanced state policy and the lack of protection from the state. Current areas of support for small and medium-sized businesses are described, including taking into account European programs. State support for small and medium-sized businesses today can be considered insufficiently effective, as evidenced by a number of examples and the consequences of ill-considered decisions by the authorities, which, with the aim of stabilizing the economy in the state, inflict a tangible blow on the activities of small businesses and threaten the existence of a large part of them. The directions of management of small business structures have been determined, the primary tasks of their further functioning and development were outlined, public opinion regarding their activities was formed.

“Pioneers” of Managerial Thought: Woodrow Wilson Case

The article focuses on the diversity of the struggle for priority in the history of managerial thought. The subject of the study is the role of the American political scientist and politician Woodrow Wilson in the development of the study of public administration. The article reveals the contradiction between historical facts and prevailing ideas about the priority of W. Wilson in the development of the public administration theory. This dichotomy is proven in particular through the use of generative artificial intelligence and large language models (ChatGPT). The article analyzes the struggle for W. Wilson’s priority in the creation of the public administration science and compares it with the outwardly similar story of the discovery of genetics by Gregor Mendel. The article shows that the external similarity of the “deferred priority” in the creation of two sciences — genetics and public administration — differs significantly in the internal logic and consequences of the “rediscovery” of conceptual innovations. We can say that the “deferred priority” of the American scientist turns into a false priority, but fixed by public opinion as real. A conclusion is drawn about the relevance of W. Wilson’s case for solving modern problems of economic cybernetics. The past forms the present and future and distorting the past we can’t understand the present and predict and manage the better future.

ANALYSIS OF DISCOURSE AND TERMINOLOGY OF NATION-BUILDING IN THE CONTEXT OF THE REPUBLIC OF KAZAKHSTAN

The article analyzes the problems of nation-building terminology in policy documents, regulatory legal acts and social scientific discourse of Kazakhstan, using Norman Fairclough's three-dimensional model of critical discourse analysis. The authors divide content structure into three dimensions corresponding to Fairclough's model: text, discursive practice and sociocultural practice, which allows for a comprehensive assessment and analysis of linguistic and conceptual factors influencing the formation of national policy and public opinion. The study is aimed at identifying contradictions and discrepancies that exist in the terminological base and discursive practices. The authors offer specific recommendations for unifying terminology to improve the effectiveness of public policy in the field of nation-building.

A blue ribbon goat: the Rockefeller Commission, public opinion, and the ford administration’s intelligence reform failure

ABSTRACT After allegations of the US intelligence community conducting illegal operations that targeted American citizens, 1975 became known as the Year of Intelligence. The subject dominated national discourse and led to competing programmes of intelligence oversight proposed by Congress and the executive branch. This article examines the Ford administration’s programme that started with the Rockefeller Commission in January 1975 and ended with the issue of Executive order 11,905 in 1976. It argues that neither were enough to stave off Congress intruding on executive control of the intelligence community, because the Ford administration inaccurately measured the public’s demands for genuine reform.

LEVERAGING BIG DATA TECHNOLOGIES FOR ENHANCED PUBLIC PARTICIPATION IN PUBLIC FINANCIAL MANAGEMENT

The article is devoted to the topical issues regarding the implementation of Big Data technologies in public finance management. The application of Big Data has the potential to enhance transparency and accountability in the use of budgetary resources, increase trust in government, improve the efficiency of budget resource utilization, better understand citizens' needs, and engage the public in public finance management. The purpose of the study is to explore theoretical, methodological, and practical aspects, as well as to develop recommendations for the implementation of Big Data processing and analysis technologies to enhance public participation in public financial management. The article examines traditional methods of civil engagement in the budgetary process, identifies their disadvantages, and explores Big Data technology potential based on Computational Linguistics and Machine Learning to strengthen public participation. Developments in sentiment analysis and opinion mining have been adapted to the field of public finance. A generative model for analyzing public sentiment on social networks regarding public finance management has been constructed and tested. The approaches developed for using Big Data technologies can be implemented in the field of public finance to enhance public participation in their management as advisory tools for the realization of representative democracy and require further theoretical elaboration and practical application to improve the analysis of alternative sentiments, prevent manipulation of public opinion, and abuse within the network.

독일 특수교육의 역사에서 시대별 특수학교 명칭의 변천 과정과 시사점 탐색

Terms related to disability reflect the reflection of times and philosophies of the time, and with what conceptualized vocabulary they should be expressed has been dealt with as a major topic in academia. This paper viewed that there must have been reasonable social public opinions and purposes in the process of changing the names of special schools, and mainly paid attention to understanding the paradigm shift in special education through the foregoing. In Germany, the names of special schools attended by students with disabilities have been changed several times. In this study, the names were divided into ‘Hilfsschule’, ‘Sonderschule’, and ‘Förderschule’ and the process of changing the names was generally examined. Whereas ‘Hilfsschule’ was introduced in that it was a positive term on humanitarian grounds, ‘Sonderschule’ helped organize 10 different types of special schools into one school system and establish a thoroughly independent school system. The name ‘Förderschule’, which has represented special schools in Germany since the 2000s, can be seen as emphasizing the need for special educational support. ‘Special schools for students with disabilities’ are being changed into ‘support centers for all students who need support.’ As concerns about terms that reflect the trends of the times are a common topic regardless of eras or societies, it is expected that examining the process of changing the names of special schools in Germany will have many implications for us as well.

ELECTION RESULT PREDICTION

This study utilizes Text Blob for sentiment analysis of social media and news data to predict election results. By analyzing sentiment polarity, a comprehensive understanding of public opinion towards political entities is obtained. Machine learning algorithms are employed to build predictive models using historical election data. Results demonstrate the effectiveness of sentiment analysis in enhancing prediction accuracy compared to traditional methods. This research has implications for political campaigns and policymakers in gauging public sentiment and anticipating electoral outcomes. Keywords— Text Blob, sentiment analysis, election prediction, social media, machine learning.