Opinion Change Research Articles

Putting partisan influence into political context: How initial policy popularity and party attachment shape the effect of party cues

Parties and their actions almost always shape the preferences, attitudes, and behaviour of their voters. However, does partisan influence over public opinion apply to all policy proposals regardless of their initial popularity and to all voters regardless of their degree of partisan attachment? This question is addressed in the real-world context of Finland, where the government enacted two reforms at the same time: an initially popular reform extending the age of compulsory education, and an initially unpopular removal of the ‘retirement tube’ for older laid-off workers. An original panel survey asked respondents about their attitudes before and after the government actions, finding that while voters of government parties increasingly tended to support the enacted policies, the magnitude of opinion change depended on voters’ initial policy preferences and party attachment. Strong party attachment led to government voters increasing their support for a reform that they initially opposed. In contrast, those with weaker partisan attachments tended to alter their preferences for an initially popular reform. These findings are relevant for understanding partisan influence over public opinion in a broader political context.

Notification of changes in taxonomic opinion previously published outside the IJSEM. List of Changes in Taxonomic Opinion no. 38.

Notification of changes in taxonomic opinion previously published outside the IJSEM. List of Changes in Taxonomic Opinion no. 38.

Using opinion dynamics to identify groups for targeted intervention in lifelong learning: A case study of SkillsFuture in Singapore

In this paper, we explore the use of opinion dynamics models to examine changes in opinions of lifelong learning, and to identify groups of people for targeted intervention to improve their reception to lifelong learning. This method has a multitude of potential applications related to clustering and segmentation. Singapore’s initiative for lifelong learning, SkillsFuture, serves as a case study for the application of the technique. We first found a positive correlation between how motivated people are to learn and a negative correlation between how much people know about SkillsFuture opportunities, with respect to their reception to SkillsFuture courses. Then, we used an opinion dynamics model to model the evolution of opinions to produce clusters of people whose opinions will converge. The clusters were then grouped into three groups: those with the largest increase, largest decrease and a middle group. Further examining the covariates of the people in each cluster (e.g., age, last drawn salary, etc.), we propose organizing sharing sessions for the group with the largest increase, intervention for the group with the largest decrease, and gathering more information about the motivations of the middle group.

(Mis)Informing the public? The public's responsiveness to reliable and unreliable information in illiberal information environments

AbstractBackgroundPublic opinion has a dynamic relationship with policy and real‐world outcomes in liberal settings where reliable information is abundant. In these settings, the public continuously updates its opinions with reliable policy‐relevant information, and the changes in public opinion go on to affect policy and outcomes. It is unknown whether this dynamic exists in illiberal settings where the public's access to reliable information is heavily restricted.ObjectivesThis article advances a theory of public opinion's dynamic relationship with policy and outcomes that applies to illiberal settings.MethodsOur study examines a vital public good in one of the world's most restrictive information environments and estimates a dynamic model of relationships among three variables—public opinion, policy, and outcomes—with a focus on public opinion and outcomes as the key dependent variables. The analysis looks at air pollution remediation in 274 Chinese localities.ResultsWe find that public opinion reacts to objective air pollution outcomes and not to misleading information that downplays air pollution severity, which suggests the public can accurately evaluate the reliability of available information. We also find that local public opinion's impact on local air pollution is substantively meaningful on timescales as short as 1 to 2 years, indicating that the additional policy effort prompted by public opinion change is sufficient to yield tangible real‐world outcomes even in the short term.ConclusionPublic opinion has a dynamic relationship with policy and real‐world outcomes even in highly illiberal settings. We argue that these findings are likely to generalize across issue domains with outcomes that can be directly observed by the public.

Validation of the Greek version of the contact lens dry eye questionnaire-8 (CLDEQ-8)

PurposeContact lens discomfort (CLD) has been cited as one of the prime reasons for discontinuing contact lens wear. The CLDEQ-8 was created in 2008 to reflect status of and change in overall opinion of soft contact lenses. The purpose of this study is to examine the validity and reliability of a Greek version of the Contact Lens Dry Eye Questionnaire-8 (CLDEQ-8), using Rasch statistical analysis. MethodsThis an observational prospective study of 150 consecutive patients who received soft contact lenses and were followed through with a single follow-up appointment up to a year following their initial one. The patients filled in the Greek versions of the CLDEQ-8, the Ocular Surface Disease Index (OSDI) and a self-report item on their experience of contact lens use. The CLDEQ-8 was analyzed with Rasch analytic methodology. ResultsThe original scoring system of the CLDEQ-8 had to be altered regarding the response categories collapsing in fewer options in items b, 2b, 3b and item 5 of the original scale. The revised scoring system proved more psychometrically valid and the CLDEQ-8 had good measurement precision, category threshold order, targeting and differential item functioning for gender. Two alternative result indexes are proposed, a symptom intensity index and a symptom frequency index to address dimensionality issues that are evident with the items relating to symptom intensity versus the rest. Results from the CLDEQ-8 correlated with the OSDI total score and the self-reported experience of contact lens use. ConclusionsThe Greek version of the CLDEQ-8 is a psychometrically valid and reliable assessment tool for contact lens discomfort in Greek-speaking populations.

UKRAINIAN LANGUAGE TWEETS ANALYSIS TECHNOLOGY FOR PUBLIC OPINION DYNAMICS CHANGE PREDICTION BASED ON MACHINE LEARNING

Context. Automation of public opinion research will allow not only to reduce the amount of manual work, but also to obtain time slices of the results without additional efforts. Since direct interaction with respondents should be avoided, public opinion should be analyzed based on the sources of its free expression. Social networks are great for this role, as their people freely publish their thoughts or emotionally truthfully react to published information about certain events. Statistics show that data from social networks is not enough to obtain a full-fledged result, because a significant percentage of people do not use social networks. However, the automation of the study of even such a stratum of the population is already a good result for analyzing the dynamics of changes in public opinion in accordance with events in the country/world and, accordingly, for correcting the processes of public administration in the future.
 Objective of the study is to develop a technology for analyzing the flow of Ukrainian-language content in social networks for public opinion research based on finding clustered thematic groups of tweets.
 Method. The article develops a technology for finding tweet trends based on clustering, which forms a data stream in the form of short representations of clusters and their popularity for further research of public opinion. An effective approach to tweet collection, filtering, cleaning and pre-processing based on a comparative analysis of Bag of Words, TF-IDF and BERT algorithms is described. The impact of stemming and lemmatization on the quality of the obtained clusters was determined. And optimal combinations of clustering methods (K-Means, Agglomerative Hierarchical Clustering and HDBSCAN) and vectorization of tweets were found based on the analysis of 27 clusterings of one data sample. The method of presenting clusters of tweets in a short format is selected.
 Results. Algorithms using the Levenstein Distance, i.e. fuzz sort, fuzz set and levenshtein, showed the best results. These algorithms quickly perform checks, have a greater difference in similarities, so it is possible to more accurately determine the limit of similarity. According to the results of the clustering, the optimal solutions are to use the HDBSCAN clustering algorithm and the BERT vectorization algorithm to achieve the most accurate results, and to use K-Means together with TF-IDF to achieve the best speed with the optimal result. Stemming can be used to reduce execution time.
 Conclusions. In this study, the optimal options for comparing cluster fingerprints among the following similarity search methods were experimentally found: Fuzz Sort, Fuzz Set, Levenshtein, Jaro Winkler, Jaccard, Sorensen, Cosine, Sift4. In some algorithms, the average fingerprint similarity reaches above 70%. 3 effective tools were found to compare their similarity, as they show a sufficient difference between comparisons of similar and different clusters (> 20%). Based on the selected effective methods, trend analysis was successfully performed on 90,000 tweets over 7 days for 5 topics of the week using K-Means and TF-IDF for clustering and vectorization, as well as fuzz sort for cluster fingerprint comparison with a 55% similarity threshold.

Deliberation and polarization: a multi-disciplinary review

In recent years, deliberative democracy has drawn attention as a potential way of fighting polarization. Allowing citizens to exchange arguments and viewpoints on political issues in group, can have strong conflict-mitigating effects: it can foster opinion changes (thereby overcoming idea-based polarization), and improve relations between diametrically opposed groups (thereby tackling affective forms of polarization, such as affective polarization). However, these results conflict with social psychological and communication studies which find that communicative encounters between groups can lead to further polarization and even group think. The question therefore arises under which conditions deliberative interactions between citizens can decrease polarization. Based on a multidisciplinary systematic review of the literature, which includes a wide diversity of communicative encounters ranging from short classroom discussions to multi-weekend citizen assemblies, this paper reports several findings. First, we argue that the effects of communicative encounters on polarization are conditional on how those types of communication were conceptualized across disciplines. More precisely, we find depolarizing effects when group discussions adhere to a deliberative democracy framework, and polarizing effects when they do not. Second we find that the depolarizing effects depend on several design factors that are often implemented in deliberative democracy studies. Finally, our analysis shows that that much more work needs to be done to unravel and test the exact causal mechanism(s) underlying the polarization-reducing effects of deliberation. Many potential causal mechanisms were identified, but few studies were able to adjudicate how deliberation affects polarization.

Evolución de las opiniones estudiantiles sobre el ciberaprendizaje en la carrera de obstetricia

IntroductionDuring the COVID-19 lockdown, educational institutions implemented online learning, revealing that some university teachers and students were not prepared for this transition. Additionally, students were unable to attend clinical preceptorship in healthcare settings. The objective of this study was to analyze the evolution of agreement-disagreement levels among obstetrics students with virtual learning and identify variables that can predict changes in opinion. MethodA predictive longitudinal study was conducted using a Likert-adapted and validated survey administered to students at the beginning and end of the lockdown. Bayesian statistical analysis was performed using ordinal regression model analogs due to their advantages over frequentist methods. ResultsOpinions evolved from disagreement at the beginning to neutral opinions in half of the survey items at the end. It can be predicted that students will disagree with online learning when they are in their final semesters. ConclusionsAgreement with teleeducation improved due to its association with multiple advantages and the computer skills acquired during this period, especially among students. However, students in their final semesters expressed disagreement with online learning, which can be attributed to the lack of clinical preceptorship with patients in healthcare settings. Digital competencies must be improved among students and teachers to take advantage of the benefits offered by online learning.

Dynamic Representation Learning with Temporal Point Processes for Higher-Order Interaction Forecasting

The explosion of digital information and the growing involvement of people in social networks led to enormous research activity to develop methods that can extract meaningful information from interaction data. Commonly, interactions are represented by edges in a network or a graph, which implicitly assumes that the interactions are pairwise and static. However, real-world interactions deviate from these assumptions: (i) interactions can be multi-way, involving more than two nodes or individuals (e.g., family relationships, protein interactions), and (ii) interactions can change over a period of time (e.g., change of opinions and friendship status). While pairwise interactions have been studied in a dynamic network setting and multi-way interactions have been studied using hypergraphs in static networks, there exists no method, at present, that can predict multi-way interactions or hyperedges in dynamic settings. Existing related methods cannot answer temporal queries like what type of interaction will occur next and when it will occur. This paper proposes a temporal point process model for hyperedge prediction to address these problems. Our proposed model uses dynamic representation learning techniques for nodes in a neural point process framework to forecast hyperedges. We present several experimental results and set benchmark results. As far as our knowledge, this is the first work that uses the temporal point process to forecast hyperedges in dynamic networks.

Development of workshop framework empowering local stakeholders for “place strategy” in a district: An implementation at Omotesando, Tokyo

This research aims to structure the workshop framework ‘empowering local stakeholders to create a “place strategy”’, a spatial planning and management strategy for enhancing place function in a district. This strategy primarily focuses on the team-up phase for stakeholders with human and financial resources, whose mission is to bridge a backcasting vision to the next step involving others and users of the streets. Referring to the ‘link and place’ theory, originally developed in England and adapted to fit the alternative plans suggested by municipal officials at the community level, the paper establishes a toolkit and sessions for the conduct of a community-led workshop in Japan. The prototype workshop was implemented for the place strategy of Omotesando, a mixed land-use district with a famous shopping avenue in Tokyo. The validity of the workshop was examined based on opinion changes and the feedback of participants at each session. The results show that the prototype can draw the participant's consciousness on both the link and place functions, including a perspective on effective bus service. The policy option guides affected the participants' choice of flexible tactics by illustrating the relationship of link and place, which is not necessarily a trade-off.

Social Media Influencers’ Role in Shaping Political Opinions and Actions of Young Audiences

Social media influencers have become an indispensable part of social media, informing audiences, especially young ones, about various topics, such as beauty, lifestyle, or food. Recently more political influencers have emerged, and regular influencers have increasingly taken positions on political and societally relevant topics, including climate justice and gender equality. Yet, empirical evidence on how both types of influencers are perceived by their audiences and how they might impact young audiences regarding political action is scarce. Hence, the present study set out to investigate adolescents’ and young adults’ use and perception of social media influencers in the context of political information dissemination, opinion formation, and mobilization. With the help of qualitative interviews of young people in Germany (16–22 years), we show that while the mainstream media seems to still be the primary source of political information, influencers focused on politics are increasingly used to make sense of this information. The presumed impact ranges from amplifying the effects of existing opinions to opinion formation and changes in voting intentions based on the assessment provided by the influencer. Regular influencers who talk about political topics occasionally are not perceived as reliable sources of political information.

Consensus as a Nash Equilibrium of a Stochastic Differential Game

In this paper a consensus has been constructed in a social network which is modeled by a stochastic differential game played by agents of that network. Each agent independently minimizes a cost function which represents their motives. A conditionally expected integral cost function has been considered under an agent’s opinion filtration. The dynamic cost functional is minimized subject to a stochastic differential opinion dynamics. As opinion dynamics represents an agent’s differences of opinion from the others as well as from their previous opinions, random influences and stubbornness make it more volatile. An agent uses their rate of change of opinion at certain time point as a control input. This turns out to be a non-cooperative stochastic differential game which have a feedback Nash equilibrium. A Feynman-type path integral approach has been used to determine an optimal feedback opinion and control. This is a new approach in this literature. Later in this paper an explicit solution of a feedback Nash equilibrium opinion is determined.

On the Relation between Opinion Change and Information Consumption on Reddit

While much attention has been devoted to the causes of opinion change, little is known about its consequences. Our study moves a first step in this direction by looking at Reddit, and in particular to the subreddit r/ChangeMyView, a community dedicated to debating one’s own opinions on a wide array of topics. We analyze changes in online information consumption behavior that arise after a self-reported opinion change, by looking at the participation to a set of sociopolitical communities. We find that people who self-report an opinion change are significantly more likely to change their future participation in a specific subset of those communities. Specifically, there is a significant association (Pearson r = 0.46) between using propaganda-like language in a community and the increase in chances of leaving it. Comparable results (Pearson r = 0.39) hold for the opposite direction, i.e., joining these same communities. In addition, the textual content of the post associated with opinion change is indicative of which communities will be joined or left: a predictive model based only on the text of this post can pinpoint these communities with an average precision@5 of 0.20. Our results establish a link between opinion change and information consumption, and highlight how online propagandistic communities act as a first gateway to internalize a shift in one’s sociopolitical opinion.

Znaczenie wolności i godności klasy średniej w zapoczątkowaniu rewolucji przemysłowej XVIII-wiecznej Anglii

The industrial revolution initiated humanity's march towards wealth. Started in the 18th century in England, it changed the socio-institutional system of the world, which continues to this day. There are many attempts to explain the revolution. One of them, proposed by D. N. McCloskey, describes the rise of the revolution as a result of a widespread change in society's opinion about creativity, entrepreneurship and innovation. Along with political changes, this has led to an increase in the freedom and dignity of England's middle class. This provided a foothold for an explosion of innovation. However, McCloskey does not account for exactly how the increase in the dignity and freedom of entrepreneurs translates into increased innovation. The aim of the work is to explain this mechanism. Critical literature analysis and deductive reasoning were used to achieve this goal. Research shows that an increase in dignity motivates people to become more active in their own economic projects, while an increase in freedom enables an increase in the participation of the public involved in their own projects. Finally, the increase in economic activity increases the number of market participants, which forces the search for additional annuities by creating and implementing innovations.

Policy Studies Yearbook Annual Review 2022–23: Note from the editor and call for papers

<i>Policy Studies Yearbook Annual Review</i> 2022–23: Note from the editor and call for papers

To Get Vaccinated or Not? The Vaccination Decision-Making by Healthcare Professionals Working in Haematology: A Qualitative Study.

Haematological patients are more susceptible to infections. Vaccination has always been the most effective primary prevention strategy, even during the COVID-19 pandemic. However, the efficacy of vaccines for some haematological patients is low. Although vaccination of Healthcare Workers (HCWs) could protect patients from vaccine-preventable diseases, there is evidence of a high level of hesitation among healthcare workers in Italy. The aim of this study was to explore the attitudes towards vaccination of HCWs caring for haematology patients. Qualitative descriptive design was conducted. Twenty-one HCWs were interviewed. Content analysis was applied to the qualitative data. The following themes were generated from the analysis: "Trust", "Decision-making process focusing on individual health", "Decision-making process focusing on community health", "Changing opinion", and "Two sides of vaccination commitment". The most hesitant HCWs were oriented towards individual health. They perceived a lack of benefit from vaccines, feared side effects, or were influenced by negative experiences of others. In contrast, community-health-oriented HCWs showed more positive attitudes towards vaccination. Some hesitant HCWs changed their opinion on vaccination because they began to reflect on the importance of vaccination for the community. The change in opinion of some HCWs interviewed provided insight into the importance of focusing organisational efforts on collective responsibility.

The prospects for gun policy change following mass shootings

AbstractThe mass shootings in Buffalo, New York, and Uvalde, Texas in May 2022 prompted Congress to enact the first significant federal gun legislation since the 1990s. While many commentators have framed this policy change as a remarkable break from the long‐standing pattern of inaction on gun violence, I argue that political actors perceived and responded to the problem in familiar ways. Drawing on agenda setting and information processing theories, I highlight factors that suggest no fundamental alteration in how the U.S. political system responds to gun injury and death. I also point to changes in public opinion and in the interest group landscape that have the potential (in the long term) to transform the politics of gun policy. Finally, I conclude with some near‐term expectations for policy making and its effects on the issue.Related ArticlesCagle, M. Christine, and J. Michael Martinez. 2004. “Have Gun, Will Travel: The Dispute between the CDC and the NRA on Firearm Violence as a Public Health Problem.”Politics &amp; Policy32(2): 278–310.https://doi.org/10.1111/j.1747‐1346.2004.tb00185.x.Joslyn, Mark R., and Donald P. Haider‐Markel. 2018. “Motivated Innumeracy: Estimating the Size of the Gun Owner Population and its Consequences for Opposition to Gun Restrictions.”Politics &amp; Policy46(6): 827–50.https://doi.org/10.1111/polp.12276.Schwartz, Noah S. 2021. “Guns in the North: Assessing the Impact of Social Identity on Firearms Advocacy in Canada.”Politics &amp; Policy49(3): 715–818.https://doi.org/10.1111/polp.12412.

Twitter Bots in Cyber-Physical-Social Systems: Detection and Estimation Based on the SEIR Model

Bots are now part of the social media landscape, and thus, a threat to cyber-physical-social systems (CPSSs). A better understanding of their characteristic behaviors and estimation of their impact on public opinion could help improve the algorithms to identify bots and help develop strategies to reduce their influence. The cosine function-based algorithm is able to compare the similarity between tweets and restore the course of information circulation. Combined with malicious features of an account, our method could effectively detect bots. We implement SEIR model to compute tweets with the hashtag #Huawei 5G and divide the trend propagation into the following four phases: formation, fermentation, explosion, and decay of trend. Sentiment analysis revealed the change of emotion and opinion among normal users in different stages and the manipulation attempt of bots behind it. Experiment results show that bots have very limited relation to users’ stance in whole. In early phase bots could affect those who are neutral. The influence of bots declines in later stage. Polarized views can hardly be changed.

Influence via Ethos: On the Persuasive Power of Reputation in Deliberation Online

Deliberation among individuals online plays a key role in shaping the opinions that drive votes, purchases, donations, and other critical offline behavior. Yet, the determinants of opinion change via persuasion in deliberation online remain largely unexplored. Our research examines the persuasive power of ethos—an individual’s “reputation”—using a seven-year panel of over a million debates from an argumentation platform containing explicit indicators of successful persuasion. We identify the causal effect of reputation on persuasion by constructing an instrument for reputation from a measure of past debate competition and by controlling for unstructured argument text using neural models of language in the double machine-learning framework. We find that an individual’s reputation significantly impacts their persuasion rate above and beyond the validity, strength, and presentation of their arguments. In our setting, we find that having 10 additional reputation points causes a 31% increase in the probability of successful persuasion over the platform average. We also find that the impact of reputation is moderated by characteristics of the argument content, in a manner consistent with heuristic information processing under cognitive overload. We discuss managerial implications for platforms that facilitate deliberative decision making for public and private organizations online.This paper was accepted by Anandhi Bharadwaj, information systems.Funding: This research was supported in part by the University of Wisconsin Madison Office of the Vice Chancellor for Research and Graduate Education with funding from the Wisconsin Alumni Research Foundation, and by the Carnegie Mellon University Graduate Student Assembly and Provost’s Office. Computing support was provided in part by the Social Science Computing Cooperative at the University of Wisconsin Madison.Supplemental Material: Data and the online appendix is available at https://doi.org/10.1287/mnsc.2023.4762 .

77 Assessing Value of a Novel NC State University Two-Week Animal Science Study Abroad Course in Chiang Mai, Thailand for Post-Pandemic Student Education

Abstract Partially due to COVID-19 education adaptations, students and teachers alike have become more normalized to online learning platforms. While this can be valuable, it has led to an increased concern that students resist in-person meetings, lack animal and personal interactive skills and many social and cultural cues. Online platforms can allow globalized learning, but there is considerable difference between interactive study abroad education and online delivery methods. After 2 years of COVID-19 impacting study abroad programs, NC State University programs reopened in Spring 2022, although the interest and availability were understandably less than pre-pandemic years. The novel ANS 395 course Thailand: Global Animal Management Issues, Concerns and Solutions was offered Summer 2022 as a two-week, three credit hour course with 17 undergraduate students. Of these students, at least 24% had never flown, 35% had never traveled outside the USA and many more had not traveled since they were young. ANS 395 explores Thai culture and its influence on cat, dog, and elephant management as compared with North American norms. The students were housed near Chiang Mai, Thailand at a large animal sanctuary that is residence to over 100 elephants, 600 dogs and 2,000 cats. In ANS 395, students were taught and allowed to participate in basic veterinary techniques including physical exams, blood collections, IV catheter placement, suturing, medical injections, skin scraping, fecal testing, feed intake assessment, and surgical (spay/neuter) preparation. Students were able to interact with numerous animal professionals and rescued animal species in unique situations including cats in large outdoor population holding areas, semi aggressive and / or paralyzed dogs, elephants that had been severely abused, suffered landmine wounds, or were geriatric. Over 90% of the Thai population identifies as Buddhist. This presents a unique animal management learning perspective since Buddhism teaches the avoidance of all work that involves any killing of animals. Therefore, euthanasia is avoided in most veterinary cases. In contrast, many of the unique animal situations discussed above would be considered for individual humane euthanasia in North America. The novelty of ANS 395 for both instructors and students did not allow for research into how the opinions of the students on ethics and animal care may have been altered by the first offering of this course. Students were asked to Likert scale rank their Thailand animal science experience from 1(poor) to 10 (best). The average was 9/10 (n = 17). This indicates that the student’s post-pandemic valued and enjoyed their interactive study abroad experience. However, instructors did note potential post pandemic increases in social interaction difficulties. As this course develops, knowledge from 2022 will allow student assessment on ethical standpoints regarding animal care prior and post travel to understand cultural and animal management opinion changes after real world exposure.