Individual Opinions Research Articles

Complexity of manipulation and bribery in premise-based judgment aggregation with simple formulas

Judgment aggregation is a framework to aggregate individual opinions on multiple, logically connected issues into a collective outcome. It is open to manipulative attacks such as Manipulation where judges (e.g., referees, experts, or jurors) cast their judgments strategically. Previous works have shown that most computational problems corresponding to these manipulative attacks are NP-hard. This desired computational barrier, however, often relies on formulas that are either of unbounded size or of complex structure.We revisit the computational complexity for various Manipulation and Bribery problems in premise-based judgment aggregation, now focusing on simple and realistic formulas. We restrict all formulas to be clauses that are monotone, Horn-clauses, or have bounded length. We show that these restrictions make several variants of Manipulation and Bribery, which were in general known to be NP-hard, polynomial-time solvable. Moreover, we provide a P vs. NP dichotomy for a large class of clause restrictions (generalizing monotone and Horn clauses).

The Characteristics of the Religiosity of Youth in Slovakia Today

This paper discusses the current characteristics of the religiosity of young people in Slovakia based on data that were obtained in a survey as part of the research project “Perspectives of the Development of Religiosity in Slovakia”, carried out in 2017–2020. The data presented in the article pertain to several areas related to the religious lives of young people. Firstly, data on general changes in the respondents’ religiosity (such as a weakening or a strengthening) are presented, followed by data on the causes that the respondents consider having influenced these changes. Secondly, since many of the respondents claimed factors related to receiving a lot of information as such causes, the article presents data to determine to what extent the respondents paid attention to religious media in Slovakia (newspaper, radio, television, and websites). Lastly, we present the data on the respondents’ attitudes towards the moral acceptance of some themes that are religiously controversial or politically divisive in Slovak society today. We then discuss the indications that emerge from the data on the religiosity of young people in Slovakia today, overall concluding that there is often an occurrence among Slovak youth of claiming an affiliation to an official church/confession/religious institution while developing and acting on individual religious opinions or beliefs.

Barriers and Solutions in Implementing Evidence-Based Recommendations to Prevent Intraoperative Inadvertent Hypothermia: A Qualitative Study.

In this study, it was aimed to understand the barriers and solutions for operating room (OR) nurses and anesthesiologists to implement evidence-based recommendations to prevent intraoperative inadvertent hypothermia (IIH). A qualitative, inductive, and descriptive study was conducted. This qualitative interview study was conducted face-to-face with 19 participants working in OR units between February and March 2023. The interviews were analyzed using qualitative content analysis. The COREQ checklist was followed. Two main themes and five sub-themes were identified as a result of content analysis. According to the participants, barriers to IIH prevention interventions are caused by individual and organizational inefficiencies and personal opinions, and the main solution is education. Participants reported many factors that hinder IIH prevention practices. The individual characteristics of OR staff and the opinions and behavior of the institution are very important for IIH prevention.

ONLY FOUR LETTERS: ABOUT THE CORRESPONDENCE OF L.N. TOLSTOY AND A.N. OSTROVSKY IN THE HISTORY OF THE RELATIONSHIP BETWEEN TWO WRITERS

The article provides an analytical understanding of Tolstoy’s letters to Ostrovsky, consideration of their content in the projection of reviews and literary disputes of the late 1850s–1860s. A scientific commentary is given on individual facts, events and opinions in Tolstoy’s letters to Ostrovsky, the problem of the ambiguous attitude of writers to each other’s work, their interaction while working in the Sovremennik magazine is touched upon. The role of Nekrasov in establishing creative ties between the writer and the playwright is noted, the individual features and characteristics that they valued and critically perceived in each other are emphasized. The author of the article cites the opinions of contemporaries who noted similarities in the work of famous contemporaries. The paper notes the possible influence of Ostrovsky on the late Tolstoy, the latter’s recognition of the nationwide significance of Ostrovsky’s talent.

Automatically identifying customer needs in user-generated content using token classification

Users generate tremendous amounts of data on the Internet every day. This so-called user-generated content (UGC) is valuable input for organizations since it may include individual experiences, opinions, and desires with respect to the products and services they offer. To automatically process UGC, automated techniques, typically referred to as Needmining, have been developed. Existing Needmining approaches extract customer needs from UGC by binarily classifying unstructured textual data into need-content and no-need content. However, they are not able to extract the specific needs. We address this research gap by developing a decision support artifact that re-conceptualizes Needmining from a binary classification problem to a token-classification problem to extract specific needs from informative content. To achieve this, we break down customer needs into components, i.e. attributes and characteristics and develop a token classification artifact. The artifact accurately identifies the need-components and, therefore, can identify specific customer needs in user-generated content. We organize and discuss the value of the artifact's output and further enrich the model with sentiment data to distinguish relevant needs. If applied, the artifact can realize efficiency gains for decisionmakers in the field of product development as it automatically and quickly identifies relevant consumer needs.

Use of adapted or modified methods with people with dementia in research: A scoping review.

People with dementia are excluded from research due to methodological challenges, stigma, and discrimination. Including perspectives of people with dementia across a spectrum of abilities is essential to understanding their perspectives and experiences. Engaging people living with dementia in qualitative research can require adaptation of methods.Qualitative research is typically considered when researchers seek to understand the perspectives, lived experiences, or opinions of individuals' social reality. This scoping review explores current use of adapted methods with people with dementia in qualitative research, including methods used and impacts on the engagement as it relates to meeting accessibility needs. This review considered rationales for adaptations provided by authors, particularly whether authors identified a human rights or justice rationale for adapting methods to promote accessibility and engagement.This review began with a search of primary studies using qualitative research methods published in English in OECD countries from 2017 to 2022. Two reviewers screened titles and abstracts for inclusion. Full texts were reviewed, and data from included studies were extracted using a pre-determined chart. Content analysis of rationales was conducted and reviewed by all authors. Studies were assessed for findings related to impacts of adapted methods.Twenty-eight studies met inclusion criteria. Adaptations to qualitative research methods ranged from minor changes, such as maintaining a familiar interviewer, to more extensive novel methods such as photo-elicitation techniques. Twenty-seven studies provided a rationale for adapting their methods. No studies assessed impacts of their methodology on engagement or accessibility. Five studies observed that their methodology supported engagement.This review helps understand the breadth of adaptations that researchers have made to qualitative research methods to include people with dementia in research. Research is needed to explore adaptations and their impact on engagement of persons with dementia with a range of abilities and backgrounds.

Opinions of hearing-impaired individuals about social media: A preliminary study

Objectives: The study examined the opinions of hearing-impaired individuals about the content on social media platforms, their social media usage tendencies, and their feelings, thoughts, and experiences during their use. Patients and Methods: Forty individuals aged 18 years and older who are native Turkish speakers diagnosed with hearing loss regardless of the type and degree of hearing loss participated in this cross-sectional survey study between November 1, 2021, and September 1, 2022. Individuals with advanced vision problems and illiterate individuals were excluded from the study. The questionnaire consisted of four sections: (i) demographic data and hearing loss characteristics; (ii) social media usage and purposes; (iii) opinions about the content on social media; and (iv) feelings, thoughts, and experiences about social media. Responses were evaluated on a 5-point Likert-type scale. Results: The most common purposes of using social media were doing research and getting information about hearing loss and the technologies they use. Of the participants, 45.5% stated that they do not prefer their devices to be seen in the photos they share on social media platforms and that they are undecided about the ease of use of existing social media platforms for the hearing impaired. Conclusion: It is important to determine what hearing-impaired individuals feel about hearing loss and technologies, both to guide hearing care professionals and health institutions in creating content on these issues and to improve these platforms.

The Impact of Extreme Precipitation Events and Their Variability on Climate Change Beliefs in the American Public

Abstract Although scientists agree that climate change is anthropogenic, differing interpretations of evidence in a highly polarized sociopolitical environment impact how individuals perceive climate change. While prior work suggests that individuals experience climate change through local conditions, there is a lack of consensus on how personal experience with extreme precipitation may alter public opinion on climate change. We combine high-resolution precipitation data at the zip-code level with nationally representative public opinion survey results (n = 4008) that examine beliefs in climate change and the perceived cause. Our findings support relationships between well-established value systems (i.e., partisanship, religion) and socioeconomic status with individual opinions of climate change, showing that these values are influential in opinion formation on climate issues. We also show that experiencing characteristics of atypical precipitation (e.g., more variability than normal, increasing or decreasing trends, or highly recurring extreme events) in a local area are associated with increased belief in anthropogenic climate change. This suggests that individuals in communities that experience greater atypical precipitation may be more accepting of messaging and policy strategies directly aimed at addressing climate change challenges. Thus, communication strategies that leverage individual perception of atypical precipitation at the local level may help tap into certain “experiential” processing methods, making climate change feel less distant. These strategies may help reduce polarization and motivate mitigation and adaptation actions. Significance Statement Public acceptance for anthropogenic climate change is hindered by how related issues are presented, diverse value systems, and information-processing biases. Personal experiences with extreme weather may act as a salient cue that impacts individuals’ perceptions of climate change. We couple a large, nationally representative public opinion dataset with station precipitation data at the zip-code level in the United States. Results are nuanced but suggest that anomalous and variable precipitation in a local area may be interpreted as evidence for anthropogenic climate change. So, relating atypical local precipitation conditions to climate change may help tap into individuals’ experiential processing, sidestep polarization, and tailor communications at the local level.

Sentiment Analysis Based on Performance of Linear Support Vector Machine and Multinomial Naïve Bayes Using Movie Reviews with Baseline Techniques

Movies are the better source of entertainment. Every year, a great percentage of movies are released. People comment on movies in the form of reviews after watching them. Since it is difficult to read all of the reviews for a movie, summarizing all of the reviews will help make this decision without wasting time in reading all of the reviews. Opinion mining also known as sentiment analysis is the process of extracting subjective information from textual data. Opinion mining involves identifying and extracting the opinions of individuals, which can be positive, neutral, or negative. The task of opinion mining also called sentiment analysis is performed to understand people’s emotions and attitudes in movie reviews. Movie reviews are an important source of opinion data because they provide insight into the general public’s opinions about a particular movie. The summary of all reviews can give a general idea about the movie. This study compares baseline techniques, Logistic Regression, Random Forest Classifier, Decision Tree, K-Nearest Neighbor, Gradient Boosting Classifier, and Passive Aggressive Classifier with Linear Support Vector Machines and Multinomial Naïve Bayes on the IMDB Dataset of 50K reviews and Sentiment Polarity Dataset Version 2.0. Before applying these classifiers, in pre-processing both datasets are cleaned, duplicate data is dropped and chat words are treated for better results. On the IMDB Dataset of 50K reviews, Linear Support Vector Machines achieve the highest accuracy of 89.48%, and after hyperparameter tuning, the Passive Aggressive Classifier achieves the highest accuracy of 90.27%, while Multinomial Nave Bayes achieves the highest accuracy of 70.69% and 71.04% after hyperparameter tuning on the Sentiment Polarity Dataset Version 2.0. This study highlights the importance of sentiment analysis as a tool for understanding the emotions and attitudes in movie reviews and predicts the performance of a movie based on the average sentiment of all the reviews.

On authoritative roles of media over co-evolution of opinions in two-layer appraisal networks

Media wield the indispensable social power over the public in various contexts, such as political election, and marketing management. In this paper, we propose a novel opinion dynamics via a signed two-layer network with a time scale to model the participation of media in the co-evolution of public opinions and appraisals. We theoretically analyze the roles of media through investigating the topological evolution of strongly connected components (SCCs). We predict that the media play authoritative roles on both opinion bound and co-evolution rate. The maximal opinion convergence state among the media layer and the sink SCCs of individual layer will finally restrict the opinions of individuals in the non-sink SCCs. The faster updates of media’s comments will guide a faster opinion forming process. Besides, we discuss the factors of promoting and suppressing the roles of media, and find that the property of structural balance is significant for media in enhancing their potential to facilitate the public to share the bipartite consensus opinions with media. Our findings witness their sociological meanings in an empirical voting network.

서예진흥법 내실화를 위한 서예교육 전문인력 양성 방안 제언

This article suggested ways to train and promote calligraphy education professionals to internalize the basic plan for calligraphy promotion.
 First of all, the current status and necessity of training professionals, and the opinions of related institutions and individuals were comprehensively confirmed. Currently, the training of professionals in the field of calligraphy is centered on universities (graduate schools), and only one university is currently in existence, and since graduate schools assist in the role of universities, it has been confirmed that the size of training and production of calligraphy education professionals is gradually decreasing. On the other hand, most institutions and individuals are aware of the importance of fostering calligraphy education professionals, and suggested the establishment of training institutions, standard curriculum and textbook development, treatment and employment issues after completion of training.
 Next, professional manpower training and promotion measures were classified into three categories and suggested. First of all, the designation and operation of a calligraphy professional training institution were presented. The institution designation suggested cooperation and cooperation among professional educational entities, the use of local educational institutions, consultation with local governments, and operation of designated educational institutions according to the standard curriculum for training professionals.
 Second, the introduction of a qualification system for professionals in calligraphy education was suggested. Through this, the status of calligraphy education and the promotion of quality of employment, and the linkage with measures to revitalize cultural infrastructure and tourism development were described. In addition, it suggested improving operational elasticity by linking related tasks and curricula such as planning calligraphy education, establishing educational operation plans, conducting field classes, operation, and administrative tasks, establishing an organic cooperative system.
 Finally, the formation of a calligraphy promotion network and the establishment of a foundation were presented. Specifically, it was suggested to establish a comprehensive calligraphy promotion management system for long-term stabilization of calligraphy promotion policies, and to clarify and unify policies through expert forums.

Perception and attitudes of students about politically correct speech: A case study from the spectrum of diversity education

Politically correct behavior implies the use of language and the right linguistic action. Therefore, language affects the human thought process, which determines the perception of reality and the individual’s actions. These measures of language that reform and sensitize people to justice and inclusion have raised many research questions. At the linguistic level, the concept aims to exclude any discriminatory use of language from discourse. From a sociological aspect, political correctness implies that speech that does not lead to discrimination and does not destroy a person’s identity. While, on the other methodological side, political correctness still implies the renewal of the culture of learning, that is, the redefinition of the educational paradigm. The paper aims to examine the perception of students of different fields of study about political correctness in the language and to compare the obtained data to raise awareness of the importance of using political correctness. 68 students of the Humanities and Social Sciences at Split and Libertas International University participated in the research. The work is based on the hypothesis that there are significant statistical differences in individual opinions regarding the direction of the study. Research has shown that more students of International Relations and International Business are warned about political correctness in the language because it is related to their profession, as opposed to the students in Split who study German language and literature. This was to be assumed, considering the different goals of the outcomes of the mentioned studies. The paper can be a guide for future similar research on a larger population, as well as a form for raising awareness of the importance of the concept of diversity and its implementation in higher education.

Personal Cognition and Implicit Constructs Affecting Preferential Decisions on Farmland Ownership: Multiple Case Studies in Kediri, East Java, Indonesia

Farmland ownership is a critical issue for sustainable agriculture since it affects short-term productivity and the long-term stability of the sector. However, existing literature largely focused on immediately simplifying individual opinions through statistical methods, neglecting how implicit values could drive preferential ownership decisions. Therefore, this study aimed to understand the driving factors underlying decisions on farmland ownership, especially when there are cognitive factors that induce hidden constructs in individual preferences. This research, to observe the cognition and implicit values leading to ownership decisions, applied the Repertory Grid Technique (RGT) with subsequent Principal Component Analysis (PCA). Taking the multiple case studies of three villages in Kediri, East Java, Indonesia, this study involved 40 farmland owners. The RGT revealed a staggering 85 constructs leading to six ownership decisions: keep farming, buying, joint farming, leasing, selling, and converting. In general, the driving forces were distinguished into landowners’ household profile, sustainability-related (community and social conditions), spatial (farmland conversion and accessibility), and economic aspects. Based on PCA, “buying” and “keep farming” shared several driving forces and led to sustainable farming. In contrast, “joint farming”, “leasing”, “selling”, and “converting” were found to threaten farming sustainability. In addition, this study offers in-depth insights into the driving factors of different preferential ownership decisions according to the cognition and implicit values of individual landowners, allowing policymakers and other stakeholders to tailor policies and strategies to context-specific farmland ownership issues in pursuing sustainable agriculture.

Data Analytics and Personalized Marketing Strategies in E-commerce Platforms

The purpose of this study is to identify the most adapted digital data analysis tools for developing individual marketing strategies in the e-commerce segment. In the study the following ranking methods were used: the cross-expert rating (based on individual opinions of 15 specialised organisations) and arbitration rating of the most relevant resource - G2.com. Subsequently, a comparative analysis of the leading E-Commerce Analytics applications was performed in order to obtain the ranking results. Using a methodology that took into account the expert ratings, cross- and arbitrage ratings, as well as the user feedback, it was found that the Glassbox was the best option for large enterprises, particularly, for large e-businesses. Google Analytics, on the other hand, is more popular among smaller companies and is considered a more versatile tool for data analysis. The importance of choosing the right tool for data analytics in e-commerce was also highlighted in the study, as the wrong choice can lead to financial losses and loss of investment. Future researches in this area include the creation of universal algorithms for selecting data analytics software solutions, expanding the range of data analytics applications, and more detail in understanding the specific needs of e-commerce platforms.

Fluoroscopic image-based behavior analysis can objectively explain subjective expert assessment of wire navigation skill.

Psychomotor skill and decision-making efficiency in surgical wire navigation can be objectively evaluated by analysis of intraoperative fluoroscopic image sequences. Prior work suggests that such image-based behavior analysis of operating room (OR) performance can predict performer experience level (R2 = 0.62) and agree with expert opinion (the current standard) on the quality of a final implant construct (R2 = 0.59). However, it is unclear how objective image-based evaluation compares with expert assessments for entire technical OR performances. This study examines the relationships between three key variables: (1) objective image-based criteria, (2) expert opinions, and (3) performing surgeon experience level. A paired-comparison survey of seven experts, based upon eight OR fluoroscopic wire navigation image sequences, shows that the experts' preferences are best explained by objective metrics that reflect psychomotor and decision-making behaviors which are counter-productive to successful implant placement, like image count (R2 = 0.83) and behavior tally (R2 = 0.74). One such behavior, adjustments away from goal, uniquely correlated well with all three key variables: a fluoroscopic image-based analysis composite score (R2 = 0.40), expert consensus (R2 = 0.76), and performer experience (R2 = 0.41). These results confirm that experts view less efficient technical behavior as indicative of lesser technical proficiency. While expert assessments of technical skill were reliable and consistent, neither individual nor consensus expert opinion appears to correlate with performer experience (R2 = 0.11).

Multidimensional attributes expose Heider balance dynamics to measurements

Most of studied social interactions arise from dyadic relations. An exception is Heider Balance Theory that postulates the existence of triad dynamics, which however has been elusive to observe. Here, we discover a sufficient condition for the Heider dynamics observability: assigning the edge signs according to multiple opinions of connected agents. Using longitudinal records of university student mutual contacts and opinions, we create a coevolving network on which we introduce models of student interactions. These models account for: multiple topics of individual student opinions, influence of such opinions on dyadic relations, and influence of triadic relations on opinions. We show that the triadic influence is empirically measurable for static and dynamic observables when signs of edges are defined by multidimensional differences between opinions on all topics. Yet, when these signs are defined by a difference between opinions on each topic separately, the triadic interactions’ influence is indistinguishable from noise.

A concept lattice-based expert opinion aggregation method for multi-attribute group decision-making with linguistic information

During the multi-attribute group decision-making (MAGDM) processing, the individuals often hold different opinions about the alternatives. It is necessary to aggregate the different individual opinions into a unified group opinion. In the real world, experts sometimes use linguistic expressions to evaluate attributes in uncertain environments. To address the problem of reducing the information loss of expert opinion aggregation in MAGDM, this paper proposes a MAGDM approach based on linguistic concept lattices in the context of uncertain linguistic expression. A linguistic concept lattice for multi-expert linguistic formal context is first constructed based on linguistic truth-valued lattice implication algebra, which can express both comparable and incomparable linguistic information in the decision-making process. Different expert opinions are aggregated via the extent of fuzzy linguistic concepts, which can reduce information loss in the aggregation process. Second, meet-irreducible elements in the linguistic concept lattice are introduced to reduce the computational complexity of obtaining all fuzzy linguistic concepts in the decision-making process. the distance between the intents of different fuzzy linguistic concepts is considered to enhance the rationality of linguistic decision results. In addition, the expert’s decision-making process for each alternative is visualized via linguistic concept lattices. Finally, the case study and comparative analysis illustrate the validity and rationality of the proposed approach in MAGDM with linguistic information.

Public Opinion of Commercial Space Exploration

ABSTRACT Utilizing data from a representative survey of Americans, this paper aims to understand who supports commercial space exploration. The findings show parallels to trends previously identified in who supports space exploration. In addition to confirming that knowledge about commercial space is relatively low to non-existent, the data also indicate that respondents do not believe that human spaceflight should be carried out entirely by private actors. Though typical demographic markers associated with support for space exploration, including gender, age, education, and income are identified here as being important, the data indicate that knowledge of commercial space activities is a key mediator for their influence, thereby identifying a key causal mechanism involved in the formation of individual opinion on commercial space that may also be applicable to other elements of public opinion-space studies.

Opinion formation analysis for Expressed and Private Opinions (EPOs) models: Reasoning private opinions from behaviors in group decision-making systems

In group decision-making, the expressed opinion of a social individual may be inconsistent with or even opposite to his/her own private opinion or inner thought. Expressed and private opinions (EPOs) models were then developed to study decision-making mechanisms with private opinions. However, most of the existing EPOs models assumed that the individual private opinion is often fixed, or updated by his/her own private opinion and neighbors’ expressed opinions, ignoring the behavior characteristics of social individuals. In this paper, a novel EPOs model is built under a more realistic scenario where the individual private opinions are updated by reasoning the neighbors’ private opinions from their behaviors while the expressed opinions are subject to social pressure. Meanwhile, we investigate the group opinion formation under the proposed EPOs model over a Leader–Influencer–Follower hierarchical network. The evolution process under the proposed EPOs model shows that, on the one hand, when the social pressure is monotonically increasing, group expressed opinions often reach consensus, and the consensus reaching time is closely related to the pressure increase rate. On the other hand, group private opinions and behaviors of the individuals show polarization. The simulation results reveal the sociological phenomena of “the golden mean” and “inconsistent words and deeds”, respectively.

The Immense Impact of Reverse Edges on Large Hierarchical Networks

Hierarchical networks are frequently encountered in animal groups, gene networks, and artificial engineering systems such as multiple robots, unmanned vehicle systems, smart grids, wind farm networks, and so forth. The structure of a large directed hierarchical network is often strongly influenced by reverse edges from lower- to higher-level nodes, such as lagging birds’ howl in a flock or the opinions of lower-level individuals feeding back to higher-level ones in a social group. This study reveals that, for most large-scale real hierarchical networks, the majority of the reverse edges do not affect the synchronization process of the entire network; the synchronization process is influenced only by a small part of these reverse edges along specific paths. More surprisingly, a single effective reverse edge can slow down the synchronization of a huge hierarchical network by over 60%. The effect of such edges depends not on the network size but only on the average in-degree of the involved subnetwork. The overwhelming majority of active reverse edges turn out to have some kind of “bunching” effect on the information flows of hierarchical networks, which slows down synchronization processes. This finding refines the current understanding of the role of reverse edges in many natural, social, and engineering hierarchical networks, which might be beneficial for precisely tuning the synchronization rhythms of these networks. Our study also proposes an effective way to attack a hierarchical network by adding a malicious reverse edge to it and provides some guidance for protecting a network by screening out the specific small proportion of vulnerable nodes.