Polling Data Research Articles

Abortion politics in Ireland and Iceland: in the ‘fast lane’ for liberalising attitudes?

ABSTRACT ‘The arc of the moral universe is long, but it bends towards justice.’ Social liberals have often taken Martin Luther King Jr’s words as a prophecy for their political goals, and until recently, it seemed to hold true for reproductive rights and access to abortion: public opinion data show a general international trend towards more liberal views over the past 40 years. However, a recent conservative backlash against these rights has seen attempts to limit abortion access in countries as diverse as the United States, Poland, and Malta. In this paper, we focus on trends of public opinion in two countries where the trend of liberalising abortion laws and attitudes has continued – Ireland and Iceland – and compare them against an example of a backlash case (Poland). Using data from the European Values Study and exit poll data from the 2018 Irish abortion referendum, we present evidence that attitudes towards abortion in both Ireland and Iceland have liberalised significantly compared to the global average, but find no evidence of specific shifts underway within these publics compared to those in Poland.

Emotions of Russians in 2014–2024

The article presents the results of analyzing data from the 2014–24 all-Russian public opinion polls on 16 emotions experienced personally and observed in others. The hierarchy and dynamics of mean values of positive and negative emotion indices were investigated. Changes in distinct emotions in 2020–24 were assessed using regression analysis. It has been found that pride and other self-esteem emotions are well expressed in the Russian emotional climate, both in self-reports and in responses about other peoples feelings. In 2014–22, national pride was inferior to collective resentment in the hierarchy of emotions; subsequently, the ratio reversed. In 2020–21, during the COVID-19 pandemic, there was a significant exacerbation of negative emotions, such as frustration, antagonistic feelings, and fatigue. Particularly significant was the increase in negativity observed by respondents in their social environment. Contrary to our expectations, the polling data for 2022–24 did not reflect a surge of negative emotions in connection with Russia’s military actions against Ukraine. Frustration levels rose briefly in the spring of 2022; new spikes weren’t recorded thereafter. Mentions of depression and antagonistic emotions have become significantly rarer in this period; positive emotions increased dramatically and began to dominate over negative ones. Psychological arousal is mainly related to the strengthening of collective self-esteem. Secondary trends indicate psychological and moral discomfort of a small part of Russians at this time. Survey data indicate an increased level of collective shame and confusion recognized in other people. One more feature is the reduced level of individual self-esteem.

Pious people, patronage jobs, and the labor market: Turkey under Erdoğan’s AKP

AbstractIn fragmented societies, electoral competition often entails using public office to advance group interests. Using individual-level polling data from 2012 to 2018, we analyze whether age cohorts entering the labor market before and after the religiously conservative Justice and Development Party (AKP) assumed power in Turkey experienced different public employment outcomes based on their religion and religiosity. Our analysis reveals that under the AKP rule, pious Sunnis (who constitute a large part of the society) significantly increased their presence in public sector employment (notably among women) and in high-status private jobs (notably among men). Furthermore, the subset of highly religious Sunnis (only 9.3% of the population) improved their likelihood of being employed in the public sector compared to other pious Sunnis and everyone else. Our findings are likely to be driven by the lifting of the headscarf ban in public employment and AKP’s strategic use of public employment and resources to reward like-minded groups in both the public and private spheres.

Partisan habitual voters in South Korea: Employing Random Forests to understand Korean voters' electoral choices

AbstractObjectiveThis study investigates whether recent political events in South Korea, such as a presidential impeachment and changes in leadership, have caused a realignment of voters' political affiliations. We aim to determine whether political party allegiance has transitioned into a pattern of habitual voting in the last ten years.MethodsEmploying a Random Forest model based on machine learning approaches, we examined polling data from the last ten years of Korean presidential elections. Instead of relying on hypothesis‐led methods, our analysis emphasizes the intrinsic characteristics of the data to uncover crucial elements affecting voter behavior in each election.ResultsOur results reveal a considerable consistency in voting patterns over the past decade, implying that allegiance to political parties has turned into a habitual behavior. Significant factors affecting voter choices in the 2022 election were also recognized as indicators of election outcomes five and ten years prior.ConclusionThe study reveals that voter behavior in South Korea remains stable despite notable political changes, primarily influenced by habitual elements rather than substantial changes in party loyalty. This suggests that political allegiance has become ingrained as a habitual behavior for Korean voters.

Russians’ Attitudes Towards the War in Ukraine

ABSTRACTThe Russian invasion of Ukraine has caused considerable military casualties on both sides and widespread harm to Ukrainian civilians. While polls suggest that a slim majority of Russians endorse the invasion, the factors underpinning this support remain uncertain. We investigated factors associated with support for the war among Russians. In three large, diverse, samples of Russian adults (total N = 2856), we extend the dual process motivational model to the context of international warfare, focusing on two key ideologies: right‐wing authoritarianism (RWA) and social dominance orientation (SDO). Consistent with polling data, we find that approximately half of the participants support the war. Across studies, RWA, especially its submission facet, emerges as a strong and consistent predictor of increased support for the war in Ukraine. In contrast, the associations with SDO are weaker and more inconsistent, with anti‐egalitarianism playing only a minor role in opposing peace efforts. Additionally, factors such as Russian identification, nationalism, group efficacy, war‐related misperceptions and collective narcissism also contribute to war support. Our findings suggest that Russian support for the war may reflect broader support for the existing regime with backing for the military intervention serving as a demonstration of loyalty to Vladimir Putin and his government.

Navigating New Waters: Russian Military Aggression on Ukraine and Effects on the Visegrad Group

In this article, the author examines the dynamic evolution of the Visegrad Group (V4) countries in response to Russia's war on Ukraine. Although V4 cooperation is deeply rooted in shared historical experiences, recent geopolitical challenges have revealed significant differences among member countries. Poland and the Czech Republic are strongly supportive of Ukraine and oriented towards NATO, while Hungary and Slovakia are more ambivalent, creating internal tensions. The author examines the factors that shape national identities and their influence on these divergent responses, highlighting that these factors have implications for the future of the V4 countries. The researcher used mixed methods to analyse official documents, political speeches and opinion poll data from the V4 countries, to examine the impact of Russia's invasion of Ukraine on V4 unity and solidarity, and to consider the implications for the future of the V4 countries. The findings point to a fragile unity and growing concerns about the V4's ability to respond coherently to external threats.

Green Giants: Competition and Climate Monopoly

This article provides a glimpse of how climate monopolists might emerge, consolidate economic power, and call forth the need for nimble procompetitive tweaks in dynamic (but not dynamic enough) climate markets. It tracks an under-recognized source of U.S. EV-sector sluggishness: the purportedly market-galvanizing performance of Tesla. Tesla’s dual dominance in both EV sales and high-speed EV charging means that prospective EV purchasers have had little alternative to Tesla’s luxury models. Moreover, polling data suggest that Tesla has foisted self-driving technologies on an unreceptive yet captive EV consumer base, generating unrivaled data streams which reinforce the firm’s market power.

Kpop: a kernel balancing approach for reducing specification assumptions in survey weighting

Abstract With the precipitous decline in response rates, researchers and pollsters have been left with highly nonrepresentative samples, relying on constructed weights to make these samples representative of the desired target population. Though practitioners employ valuable expert knowledge to choose what variables X must be adjusted for, they rarely defend particular functional forms relating these variables to the response process or the outcome. Unfortunately, commonly used calibration weights—which make the weighted mean of X in the sample equal that of the population—only ensure correct adjustment when the portion of the outcome and the response process left unexplained by linear functions of X are independent. To alleviate this functional form dependency, we describe kernel balancing for population weighting (kpop). This approach replaces the design matrix X with a kernel matrix, K encoding high-order information about X. Weights are then found to make the weighted average row of K among sampled units approximately equal to that of the target population. This produces good calibration on a wide range of smooth functions of X, without relying on the user to decide which X or what functions of them to include. We describe the method and illustrate it by application to polling data from the 2016 US presidential election.

Attention-aware with stacked embedding for sentiment analysis of student feedback through deep learning techniques.

Automatic polarity prediction is a challenging assessment issue. Even though polarity assessment is a critical topic with many existing applications, it is probably not an easy challenge and faces several difficulties in natural language processing (NLP). Public polling data can give useful information, and polarity assessment or classification of comments on Twitter and Facebook may be an effective approach for gaining a better understanding of user sentiments. Text embedding techniques and models related to the artificial intelligence field and sub-fields with differing and almost accurate parameters are among the approaches available for assessing student comments. Existing state-of-the-art methodologies for sentiment analysis to analyze student responses were discussed in this study endeavor. An innovative hybrid model is proposed that uses ensemble learning-based text embedding, a multi-head attention mechanism, and a combination of deep learning classifiers. The proposed model outperforms the existing state-of-the-art deep learning-based techniques. The proposed model achieves 95% accuracy, 97% recall, having a precision of 95% with an F1-score of 96% demonstrating its effectiveness in sentiment analysis of student feedback.

From landslide to mudslide: The strategic marketing mistakes of the 2020–2023 New Zealand Labour Government

This article explores how a political party’s fortunes can change extremely quickly, by examining the strategic errors behind the Labour Party’s 2023 loss in New Zealand. In October 2020, Prime Minister Jacinda Ardern and the Labour Party of New Zealand won a landslide majority. This secured a once in a generation chance to deliver transformational change. However, just over 2 years later, Ardern exited following a profound drop in popularity. Although a respected minister, Chris Hipkins, took over, the party then suffered a massive defeat. We apply a playbook developed for the 2020 election to identify the reasons behind such a downturn in fortunes, noting the speed of change of voter priorities and Labour’s failure to develop a clear vision or pivot to address changed priorities. We draw on multiple sources of data, including party policies, communications, polling data and the public engagement survey Vote Compass. This confirms that governments, to maintain support, must utilise appropriate market research and engage in careful political marketing planning, starting with understanding voter expectations from the last election.

Economic Development and Adolescent Wellbeing in 139 Countries

There is a positive association between the level of economic development and national levels of overall life satisfaction (OLS) in the adult population, with decreasing marginal returns. However, research shows no association in early adolescence and a negative association in middle adolescence. We hypothesize that this is due to the exclusion of low-income countries, where adolescent wellbeing is rarely collected. 2015–2019 Gallup World Poll data from 139 countries in middle adolescence (age 15–17; n 36,907) were analysed using linear regression to study the association between country levels of economic development and OLS, positive emotions (PE), and negative emotions (NE), and how this varies across economic development levels, and gender. Variations across economic development levels were compared with those observed in the adult population. Log per-capita GDP is positively associated with OLS and PE, although in high-income countries no association is observed for PE, and among females for OLS. For NE, a negative association is observed in lower-income countries and a positive association in higher-income countries. In this age group (age 15–17), the log per-capita GDP – OLS association is stronger in lower-income countries than in higher-income countries, but this pattern reverses with age in adulthood. A nuanced relationship exists between economic development and adolescent wellbeing, which varies across measures, levels of economic development, gender, and age -including notable differences compared to adults. Our study highlights the need for improving child and adolescent wellbeing data worldwide, especially in lower-income countries, to better understand how best to support wellbeing globally.

The Relative Effects of a Scandal on Member Engagement in Rites of Integration and Rites of Passage: Evidence from a Child Abuse Scandal in the Catholic Archdiocese of Philadelphia

Organizational research has documented that scandals lead to negative aggregate stakeholder reactions. There is little reason to believe, however, that the effects of a scandal are homogenous across different types of engagement. We therefore compare the effects of a scandal on member engagement in two types of rites at normative organizations: rites of integration and rites of passage. Rites of integration focus on the community, celebrate organizational values, and help strengthen organizational identification; they are thus enacted more by core members. Rites of passage focus on the individual, celebrate transition between social roles, and require only occasional engagement; they are thus enacted by core and peripheral members. Because of these differences, we hypothesize that a normative organization’s implication in a scandal affects rites of passage more negatively than rites of integration, but that this effect depends on scandal prevalence among neighboring organizations, organizational age, and organizational size. We test our hypotheses in the context of a child abuse scandal in the Catholic Archdiocese of Philadelphia. Using yearly parish-level data from 1990 to 2010, we find that a parish’s implication in the scandal was associated with a larger decline in rites of passage (marriages, baptisms, and funerals) than in rites of integration (mass attendance). This difference was reversed with the increase in scandal prevalence. Furthermore, rites of integration were more resilient than rites of passage at older and larger parishes. To help rule in the plausibility of our organization-level theory, we present a simulation grounded in individual-level polling data from the context. Supplemental Material: The online appendix is available at https://doi.org/10.1287/orsc.2022.16682 .

Driving Business Growth from Research to Innovation in The Deployment of Business Intelligence

This research evaluates a company's development and performance based on its intelligence and BI utilization. A study using quantitative poll data from numerous firms examines the relationship between leveraging business knowledge, promoting innovation, and important performance metrics. The findings demonstrate that BI adoption and receptivity to new ideas improve corporate development. Companies that invest heavily in business intelligence (BI) programmes and foster innovation generally outperform their rivals in sales, earnings, and market share. Creative thinking and business knowledge are crucial to corporate success, according to the findings. These gives workers’ suggestions on how to work faster and more creatively. More research, sector-specific analysis, and continuing studies are needed to determine how innovation culture and BI adoption effect firm performance. Finally, this research adds to what is already known about how BI adoption and innovation culture effect firm performance in today's competitive business environment.

Predictors of Life Satisfaction: A Nationwide Investigation in Iran

Iran is a developing country with low levels of economic development and globalization and is ruled by a theocratic government. To address the lack of national research on well-being in Iran, this retrospective observational study aims to examine life satisfaction and its main determinants among Iranian adults. Using World Gallup Poll data collected between 2006 and 2017, we examined life satisfaction as a cognitive aspect of subjective well-being in relation to various factors. Our results show that income is the strongest predictor of life satisfaction, followed by standard of living, gender, social support, age, negative affect, and education. In developing countries such as Iran, which face significant economic, political, and social challenges, individuals prioritize the satisfaction of basic needs by emphasizing factors such as the socioeconomic status. In contrast, developed countries with established welfare systems may emphasize other values such as social connections and healthy lifestyle behaviors as key factors in life satisfaction. This study contributes to a deeper understanding of the determinants of life satisfaction in Iran and provides insights for future research and policy making.

Social Media and Politics : the Potential of Social Media for Education and Civic Engagement

This paper looks at the links between educating people and getting involved in politics to show how social media can help these areas. This study looks into how online social networks make it easier for people to get involved in politics in ways other than voting. This study looks at how social media affects democratic accountability, information sharing, and public participation by using ideas from organisational studies, media studies, and political science. This study looks into how young Jordanians' use of social media affects their voting habits, their membership in political groups, and their involvement in protests. This study uses quantitative analysis of poll data to show that among Jordanian teens and young adults aged 18 to 30, there are strong links between being politically active and using social media. The results show that social media can help young people become more publicly active, informed, and involved. However, polarisation and false information can also make this harder. Because gender affects the link between political participation and social media use, it is important to use targeted strategies that aim to reduce demographic differences. According to the study, social media can have an effect on current politics. It also calls for smart use of social media to avoid any bad effects.

AI in International Politics

Abstract: Over the past ten years, artificial intelligence (AI) has significantly impacted many industries,including politics. A growing number of people are turning to artificial intelligence (AI) in politics because it offers a number of advantages that can speed up decision-making and enhance governance. Data analysis is one of the primary ways AI is being applied in politics. Data analytics is being used by governments and political parties to understand vote trends and public opinion. They canuse this to create more effective campaigns and policies that are suited to the requirements ofvarious constituencies. Additionally, AI is being used to increase the effectiveness of governmental operations. Artificialintelligence-powered chatbots and virtual assistants are being utilised to deliver information to users about various government services and programmes. Consequently, less work will need to be done by government employees, and citizens will receive information more quickly and accurately. Predicting election results is another area in politics where AI is having an impact. In order to anticipate the outcome of elections, AI algorithms are being employed to analyse a variety of elements, including polling data and social media activity. This can aid candidates and political parties in concentrating their efforts on the groups most likely to decide the election. However, the use of AI in politics also raises many concerns. One concern is the use of AI could lead to the manipulation of public opinion. There are concerns that AI algorithms could be used to create fake news or spread disinformation to influence voters.

Social Media-based Polling Data Processing using MapReduce on the Hadoop Framework

The processing of data obtained from a polling system holds significant importance as the results can serve as a reference for addressing community issues. With the escalating use of social media, Indonesia ranks fifth globally in Twitter usage. When dealing with substantial data sets, processing speed becomes a concern, prompting the author to develop a more time-efficient system for handling polling data gathered through social media. Hadoop emerges as a prime candidate for this purpose due to its two main modules: Hadoop Distributed File System (HDFS) for distributed storage and MapReduce for algorithmic computation. Through experimentation using both the wordcount program with MapReduce on Hadoop and the version without MapReduce, it was observed that MapReduce outperforms the latter in terms of data processing speed. On average, employing MapReduce on Hadoop resulted in a 1.3 times faster data processing rate compared to the method without MapReduce.

The Ukraine War as a Driver of Intraparty Conflict: Germany's Left Party and the AfD

ABSTRACT The two-year anniversary of Russia’s invasion of Ukraine affords an occasion to examine why the war has produced such deep rifts within the Left Party and the AfD. Drawing upon party documents, parliamentary proceedings, electoral and polling data and secondary literature, this article examines why Russia’s war against Ukraine proved so disruptive to both parties and explores the implications of these intraparty conflicts. Germany’s domestic politics of the Ukraine War matter given Berlin’s central role in backing the Kyiv government. This article assesses three explanations for the lack of internal unity in the Left Party and AfD regarding a new Russia policy: (a) path dependency; (b) eastern Germany, and (c) the reinforcing rather than crosscutting nature of the Ukraine War vis-à-vis the primary intraparty cleavage. It finds that the third explanation fits both Left Party and AfD cases.

The impact of voter confusion in ranked choice voting

AbstractObjectivesElection observers have expressed concerns about voter “confusion” under ranked choice voting (RCV) since the 1890s. What is the meaning of “confusing,” and how does it affect behavior? We argue (with much of the literature) that ranking candidates for public office is a cognitively complex task because of a lack of information.MethodsWe explore some observable implications of this perspective using exit poll data from the first RCV election in Santa Fe, New Mexico, in 2018.ResultsSixteen percent of voters reported having felt very (6 percent) or somewhat (10 percent) confused, and Hispanic voters were more likely to be confused than white voters. Confused voters report ranking fewer candidates, have lower confidence in ballot‐counting accuracy, and are less supportive of RCV than nonconfused voters.ConclusionsThese results raise questions about RCV's equity, participation costs for voters, ease of use, and longevity.

From bonus to burden: The cost of ruling from a new(s) perspective

AbstractStudies have repeatedly documented the cost of ruling: governing parties generally suffer electoral defeats. We approach this empirical law of political science from the perspective of another empirical law: the incumbency bonus, the fact that incumbents get more media attention than the opposition. Our claim is that the bonus constitutes an electoral liability because it reflects the critical approach of media to government power. News featuring incumbents is therefore associated with a more negative tone than news featuring the opposition. This incumbency burden in turn affects government support negatively. Empirically, we draw on an extensive news corpus covering four European countries over two decades, combined with monthly poll data. Analyses show that the incumbency burden in political news is an empirical reality, and that variations in the burden contribute substantially to predictions of government support. Finally, the negative burden effect is stronger for single‐party cabinets, but stable throughout government tenure.