Credibility Evaluation Research Articles

Competing for Trust: How Initiative and Repetition of Exposure Influence Information Credibility

ABSTRACTModern democracy often requires citizens to engage in policy debates demanding multidisciplinary knowledge. This can lead to a cognitive gap that urges citizens to seek information for decision‐making on unfamiliar policy issues. The credibility of this information is crucial, as it shapes individual perceptions and attitudes, which aggregate as public opinions. To deepen the understanding of information credibility, this study proposes an experiment leveraging theories of the continued influence effect and the illusory truth effect to answer how initiative and repetition of exposure influence the evaluation of information credibility. 1,400 participants will be recruited and requested to rate the credibility of opposing arguments regarding a fictitious referendum provided with varying orders and numbers. The result is expected to show a positive causality between exposure initiative, information repetition, and information credibility. The findings will aid in promoting well‐informed democratic deliberation in an era of political polarization.

The impact of socio-demographic factors on web credibility assessment

The aim of this study is to investigate the relationship between web credibility evaluation and socio-demographic variables. A sample of 380 students from Ferdowsi University of Mashhad, Iran, was selected using stratified sampling methods. Data was collected through a questionnaire encompassing socio-demographic information and Choi items. The collected data was analysed using Spearman and Kruskal–Wallis non-parametric tests, guided by the data's characteristics (type and distribution). The findings reveal a significant association between interest, experience and academic level in determining web credibility assessments. Conversely, expertise, income, gender and age were not found to be influential factors. This is a first attempt to determine the impact of socio-demographic variables on web credibility assessment. The findings suggest that individuals from diverse age, gender and income groups could benefit from acquiring knowledge pertaining to web credibility and engaging in workshops related to this domain. Additionally, those with lower levels of experience, education and interest may derive greater value from participating in web-credibility-evaluation workshops.

Credibility Evaluation of Sand-Casting Technique for Manufacturing Francis Runner

Credibility Evaluation of Sand-Casting Technique for Manufacturing Francis Runner

Storifying instructional videos on online credibility evaluation: Examining engagement and learning

This study used video-based instruction to promote adolescents' online credibility evaluation skills and to examine whether storification of instructional videos can maintain students' situational interest and positive activating epistemic emotions during a four-lesson intervention better than non-storified instructional videos. The study also investigated whether storified instruction can enhance students' learning of online credibility evaluation skills better than non-storified instruction. The learning content of the videos was equivalent, differing only in terms of storification. Students participated in either a non-storified (n = 135) or storified (n = 115) video-based instruction (4 x 45-min lesson). In each of the first three lessons, students watched an instructional video explaining one credibility evaluation strategy. In the fourth lesson, the video introduced a case requiring students to apply the taught strategies. After watching the video, students' situational interest and positive activating epistemic emotions (i.e., curiosity and excitement) were measured. Then, students practiced the taught strategies with learning tasks. Students' credibility evaluation skills were measured before and after the intervention with an online credibility evaluation task. The latent growth curve model showed that non-storified and storified videos similarly maintained students' situational interest. No decline was observed. However, a small decline in positive activating epistemic emotions was observed in both instructional conditions. Students' credibility evaluation skills improved equally across instructions. The results underline that professionally produced videos following several multimedia design principles can trigger and maintain situational interest and enhance students’ online credibility evaluation skills without the need to incorporate additional storified elements.

News bylines and perceived AI authorship: Effects on source and message credibility

With emerging abilities to generate content, artificial intelligence (AI) poses a challenge to identifying authorship of news content. This study focuses on source and message credibility evaluation as AI becomes incorporated into journalistic practices. An experiment (N = 269) explored the effects of news bylines and AI authorship on readers’ perceptions. The findings showed that perceived AI contribution, rather than the labeling of the AI role, predicted readers’ perceptions of the source and the content. When readers thought AI contributed more to a news article, they indicated lower message credibility and source credibility perceptions. Humanness perceptions fully mediated the relationships between perceived AI contribution and perceived message credibility and source credibility. This study yielded theoretical implications for understanding readers’ mental model of machine sourceness and practical implications for newsrooms toward ethical AI in news automation and production.

Cloud Manufacturing Service Composition Optimization Based on Improved Chaos Sparrow Search Algorithm with Time-Varying Reliability and Credibility Evaluation

The economic friction and political conflicts between some countries and regions have made multinational corporations increasingly focus on the reliability and credibility of manufacturing supply chains. In view of the impact of poor manufacturing entity reliability and service reputation on the new-era manufacturing industry, the time-varying reliability and time-varying credibility of cloud manufacturing (CMfg) services were studied from the perspective of combining nature and society. Taking time-varying reliability, time-varying credibility, composition complexity, composition synergy, execution time, and execution cost as objective functions, a new six-dimension comprehensive evaluation model of service quality was constructed. To solve the optimization problem, this study proposes an improved chaos sparrow search algorithm (ICSSA), where the Bernoulli chaotic mapping formula was introduced to improve the basic sparrow search algorithm (BSSA), and the position calculation formulas of the explorer sparrow and the scouter sparrow were enhanced. The Bernoulli chaotic operator changed the symmetry of the BSSA, increased the uncertainty and randomness of the explorer sparrow position in the new algorithm, and affected the position update and movement strategies of the follower and scouter sparrows. The asymmetric chaotic characteristic brought better global search ability and optimization performance to the ICSSA. The comprehensive performance of the service composition (SvcComp) scheme was evaluated by calculating weighted relative deviation based on six evaluation elements. The WFG and DTLZ series test functions were selected, and the inverse generation distance (IGD) index and hyper volume (HV) index were used to compare and evaluate the convergence and diversity of the ICSSA, BSSA, PSO, SGA, and NSGA-III algorithms through simulation analysis experiments. The test results indicated that the ICSSA outperforms the BSSA, PSO, SGA, and NSGA-III in the vast majority of testing issues. Finally, taking disinfection robot manufacturing tasks as an example, the effectiveness of the proposed CMfg SvcComp optimization model and the ICSSA were verified. The case study results showed that the proposed ICSSA had faster convergence speed and better comprehensive performance for the CMfg SvcComp optimization problem compared with the BSSA, PSO, SGA, and NSGA-III.

Design and Implementation of SaaS Online Education Management System for Expanding LMS System

The development of the education industry benefits from the continuous progress and updates of internet technology, and the organic integration of the two can further promote the emergence of the LMS (Learning Management System) system. Based on the application characteristics of the LMS system and the characteristics of the Software as a Service online education management system, a Software as a Service online education management system based on the extended LMS system was constructed. The service mode of the system was analysed, and a solution to the problem of paper formation and an analysis of the automatic paper formation algorithm in the system were provided. In addition, further research was conducted on the scores of the credibility evaluation of the system’s services under different attribute parameters. Through the correlation analysis between different attributes and the credibility evaluation scores of the Software as a Service system, it can be seen that among the selected attribute parameters, Response Time and Latency show a negative correlation with the credibility evaluation, while other parameters show a positive correlation. The Software as a Service system constructed in this article provides relevant technical solutions, which have great practical application value and have reference significance for other similar applications. It provides more support for the application and promotion of the Software as a Service (SaaS) online education management system.

Multi-source heterogeneous blockchain data quality assessment model for enterprise business activities.

Blockchain-based applications are becoming more and more widespread in business operations. In view of the shortcomings of existing enterprise blockchain evaluation methods, this paper proposes a multi-source heterogeneous blockchain data quality evaluation model for enterprise business activities, so as to achieve efficient evaluation of business activity information consistency, credibility and value. This paper proposes a multi-source heterogeneous blockchain data quality assessment method for enterprise business activities, aiming at the problems that most of the data in enterprise business activities come from different data sources, information representation is inconsistent, information ambiguity between the same block chain is serious, and it is difficult to evaluate the consistency, credibility and value of information. The method firstly proposes an entity information representation method based on the Representation learning for fusing entity category information (CEKGRL) model, which introduces the triad structure of related entities in blockchain, then associates them with enterprise business activity categories, and carries out similarity calculation through contextual information to achieve blockchain information consistency assessment. After that, a trustworthiness characterization method is proposed based on information sources, information comments, and information contents, to obtain the trustworthiness assessment of the business. Finally, based on the information trustworthiness characterization, a value assessment method is introduced to assess the total value of business activity information in the blockchain, and a blockchain quality assessment model is constructed. The experimental results show that the proposed model has great advantages over existing methods in assessing inter-block consistency, intra-block activity information trustworthiness and the value of blockchain.

Competency model development: The backbone of successful stealth assessments

AbstractBackgroundStealth assessment is a learning analytics method, which leverages the collection and analysis of learners' interaction data to make real‐time inferences about their learning. Employed in digital learning environments, stealth assessment helps researchers, educators, and teachers evaluate learners' competencies and customize the learning experience to their specific needs. This adaptability is closely intertwined with theories related to learning, engagement, and motivation. The foundation of stealth assessment rests on evidence‐cantered design (ECD), consisting of four core models: the Competency Model (CM), Evidence Model, Task Model, and Assembly Model.ObjectiveThe first step in designing a stealth assessment entails producing operational definitions of the constructs to be assessed. The CM establishes a framework of latent variables representing the target constructs, as well as their interrelations. When developing the CM, assessment designers must produce clear descriptions of the claims associated with the latent variables and their states, as well as sketch out how the competencies can be measured using assessment tasks. As the designers elaborate on the assessment model, the CM definitions need to be revisited to make sure they work with the scope and constraints of the assessment. Although this is the first step, problems at this stage may result in an assessment that does not meet the intended purpose. The objective of this paper is to elucidate the necessary steps for CM development and to highlight potential challenges in the process, along with strategies for addressing them, particularly for designers without much formal assessment experience.MethodThis paper is a methodological exposition, showcasing five examples of CM development. Specifically, we conducted a qualitative retrospective analysis of the CM development procedure, wherein participants unfamiliar with ECD applied the framework and showcased their work. In a stealth assessment course, four groups of students (novice stealth assessment designers) engaged in developing stealth assessments for challenging‐to‐measure constructs across four distinct projects. During their CM development process, we observed various activities to pinpoint areas of difficulty.ResultsThis paper presents five illustrative examples, including one for assessing physics understanding and four for the development of CMs for four complex competencies: (1) systems thinking, (2) online information credibility evaluation, (3) computational thinking, and (4) collaborative creativity. Each example represents a case in CM development, offering valuable insights.ConclusionThe paper concludes by discussing several guidelines derived from the examples discussed. Emphasizing the importance of dedicating ample time to fine‐tune CMs can significantly enhance the accuracy of assessments related to learners' knowledge and skills. It underscores the significance of qualitative phases in crafting comprehensive stealth assessments, such as CMs, alongside the quantitative statistical modeling and technical aspects of these assessments.

Transformative User Credibility Assessment on Twitter: A RNN based Heuristic Approach

Objectives: To construct a comprehensive weighted multi-dimensional model to assess the impact of influence score of Twitter users, considering the credibility based on user profile, their tweets and social interactions aiming to empower users in distinguishing fake news or misinformation. Methods: The credibility evaluation is formulated based on text analysis, user account attributes, and user social engagement. We've gathered around 100,000 tweets from 100 users using Tweepy API over a six-month duration for the purpose of evaluating credibility. The collected tweets spanned diverse professions namely politics, entertainment, business, science, sports, and trending topics. We chose to utilize a self-devised deep active learning model to classify and label the unlabelled data instead of engaging in time-consuming human annotation for the tweets we gathered. Findings: The obtained accuracy for influence score evaluation for Recurrent Neural Network, Random Forest, Naïve Bayes, Decision Tree, and Support Vector Machine are 89.03%, 79.10%, 81.59%, 73.06% and 79.45% respectively. Upon reviewing and analysing the outcomes, RNN surpassed all other models achieving an exceptional accuracy of 89.03%. Novelty: Employing a weighted multi-dimensional framework, it systematically evaluates the influence score by considering the credibility of both users and tweets within the context of Twitter. Weighted features are instrumental in capturing the relative importance of different elements, leading to a more refined and context-aware decision-making process. In contrast to earlier research, which predominantly centred on the credibility of individual tweets, our research work shifts the focus to a broader perspective, encompassing the credibility of users, their tweets and their overall social influence. By incorporating user influence score, the framework not only empower users in discerning fake news or mis-information but also elevates their ability to gauge the reliability of information, offering a nuanced approach to news credibility analysis. Keywords: Active Learning, Credibility Score, User Influence, Twitter, Machine Learning, Recurrent Neural Network

Developing a Tool for Assessing the Process of Seeking Health Information: Online Think-Aloud Method.

Nursing students can access massive amounts of online health data to drive cutting-edge evidence-based practice in clinical placement, to bridge the theory-practice gap. This activity requires investigation to identify the strategies nursing students apply to evaluate online health information. Online Think-Aloud sessions enabled 14 participants to express their cognitive processes in navigating various educational resources, including online journals and databases, and determining the reliability of sources, indicating their strategies for information-seeking, which helped to create this scoring system. Easy access and user convenience were clearly the instrumental factors in this behavior, which has troubling implications for the lack of use of higher-quality resources (e.g., from peer-reviewed academic journals). The identified challenges encountered during resource access included limited skills in the critical evaluation of information credibility and reliability, signaling a requirement for improved information literacy skills. Participants acknowledged the importance of evidence-based, high-quality information, but faced numerous barriers, such as restricted access to professional and specialty databases, and a lack of academic skills training. This paper develops and critiques a Performative Tool for assessing the process of seeking health information using an online Think-Aloud method, and explores factors and strategies contributing to evidence-based health information access and utilization in clinical practice, aiming to provide insight into individuals' information-seeking behaviors in online health contexts.

Reading Comprehension Skills and Prior Topic Knowledge Serve as Resources When Adolescents Justify the Credibility of Multiple Online Texts

This study sought to understand how well students (n = 274; M age = 12.45) were able to identify the author, the main claim, and the supporting evidence (identification performance) and to justify the author’s expertise, the author’s benevolence, and the quality of the evidence (justification performance) while reading multiple online texts. The study also examined the contribution of prior topic knowledge and basic reading skills (word recognition and reading comprehension) to students’ identification and justification performance. Students read two more and two less credible online texts about sugar effects on health. After reading each text, they responded to multiple-choice items that measured the identification and justification performance. Justifying credibility seemed more challenging for students than identifying the claim, evidence, and author. Word recognition and reading comprehension were statistically significant predictors of identification performance, whereas prior knowledge and reading comprehension were statistically significant predictors of justification performance. The findings offer new insights into the relationship between basic reading skills and credibility evaluation that can inform both theory and instruction.

A blockchain-based credibility evaluation scheme for navigational event dissemination in the internet of ships

This paper proposes a blockchain-based credibility evaluation for navigational event dissemination, which constitutes a significant functionality for the ship trust management over Internet of Ships (IoS). This enables evaluating and calculating the credibility of the navigational events announced by other ships during their navigation. The presented scheme verifies the credibility of navigational events by introducing cooperative ratings from the involved ships. Bayesian inference models are utilized as the basic estimation about the authenticity of the event, upon which the Hidden Markov Model (HMM) is leveraged to update the reputation of the relevant ships from their current reputation and the ratings they comment about the event. In addition, a Delegated Proof of Stake (DPoS) consensus mechanism based on the reputation of the ship, called R-DPoS, is designed to prioritize ships with higher trustworthiness values to be elected as witness ships, to maintain the stability and efficiency of block generation in the system. In order to validate the feasibility and effectiveness of the proposed scheme, a series of simulation experiments are conducted. The experimental results show that the proposed scheme has an accuracy of more than 80 % for navigational events in most cases, which not only effectively recognize the credibility of navigational events and update the trustworthiness value of the relevant ships, but also suppress the malicious cyber behavior of ships, enhancing the security and stability of the cyberspace of the IoS.

The Richer, the Better? Users Perception of News Credibility of Short Video News

ABSTRACT This study explores the credibility of short video news through a 3 × 2 factorial experiment on media richness and emotional intensity with 215 participants. Results show that text-based news, with lower media richness, is deemed more credible than highly rich short video news. An interaction between media richness and emotional intensity further impacts credibility assessments. Our findings suggest segmenting news by emotional intensity to refine audiovisual news credibility evaluation, offering a new direction for future research.

A comparative study of the judicial construction of scientific credibility in climate litigation

AbstractAlthough the value of climate science in the courtroom is widely acknowledged, few studies have evaluated how judges achieve a scientifically sound grounding for their rulings. Drawing insights from legal culture and science and technology studies, we compare the determination of scientific credibility in leading climate cases in Europe and the United States. Judges on both sides of the Atlantic answer similar questions about scientific facts and commonly use authoritative reports and testimonies from qualified experts. However, while judges in the Netherlands, France and Germany find value in the political mandates of international or national bodies that generate scientific reports, American judges seek to keep scientific expertise from the influence of policy considerations. We make sense of this difference by identifying two competing ideals of expertise, namely the ‘view of everyone’ ideal in Europe and the ‘view from nowhere’ ideal in the United States. Although climate science is often articulated in universalist terms, the cultural embeddedness of adjudication means that the evaluation of credibility varies by jurisdiction.

Examining adolescents’ systematic and heuristic credibility evaluation strategies of online news

ABSTRACT In an online environment where mis- and disinformation are flourishing, credibility evaluations of online news have become vital. The information processing literature suggests that individuals can either engage in systematic or in heuristic credibility evaluations, but whether this also applies to evaluations of online news and to the adolescent population is still unclear. Using an online survey (N = 338) with Flemish 15–19-year-olds, we examine adolescents’ credibility evaluation strategies. Adolescents reported using significantly more systematic evaluations than heuristic evaluations. Moreover, our findings revealed that only systematic evaluations contributed to their perceived credibility evaluation skills. Lastly, media use did not predict their credibility evaluation strategy, and attitudes and knowledge about the news only partially predicted systematic credibility evaluations. These findings are valuable for future research on credibility evaluation strategies and for practitioners and educators focusing on news literacy and credibility evaluation skills.

Credibility cues of conspiracy narratives: exploring the belief-driven credibility evaluation of a YouTube conspiracy video

ABSTRACT YouTube provides an exhaustive collection of videos that promote conspiracy narratives. Conspiracy narratives deviate from orthodox views and are grounded in non-falsifiable premises. This study aims to understand how people evaluate the credibility of conspiracy videos. Combining qualitative and quantitative methods, we examine the factors that affect users’ evaluations of the credibility of conspiracy videos in social-media settings. Qualitative findings show that users consider source, interaction, content, and their intent to follow-up on the topic as credibility cues. A quantitative analysis using a moon-landing conspiracy video as an example demonstrates that the role of credibility cues differs depending on pre-existing beliefs. Host and message cues are most relevant, with host cues more important for strong believers in the moon landing conspiracy and message cues more relevant for non-believers and moderate believers. The intention to follow up on the conspiracy topic mediates between credibility cues and users’ overall video credibility evaluation. Critical user comments about the video decrease this follow-up intention and thus contribute to a lower overall video credibility. People navigate conspiracy narratives based on information-related credibility cues, which are moderated by their previous beliefs and mediated by follow-up intention. Users who attribute credibility to conspiracy narratives perceive them as having high information quality, causing cognitive and conversational needs in users.

HCNCT: A Cross-chain Interaction Scheme for the Blockchain-based Metaverse

As a new type of digital living space that blends virtual and reality, Metaverse combines many emerging technologies. It provides an immersive experience based on VR technology and stores and protects users’ digital content and digital assets through blockchain technology. However, different virtual environments are often highly heterogeneous in terms of underlying architecture and software implementation technology, which leads to many challenges in scalability and interoperability for blockchains serving the Metaverse. Cross-chain technology is an essential technology to realize the scalability and interoperability of blockchain. However, the current cross-chain technologies all have their own merits and demerits, and there is no cross-chain solution that can be fully applied to any scenario. To this end, in the blockchain-based Metaverse, this article proposes a cross-chain transaction scheme based on improved hash timelock, HCNCT. By combining the notary mechanism, this scheme uses a group of notaries to supervise and participate in cross-chain transactions, effectively solving the problem that malicious users create a large number of time-out transactions to block the transaction channel, which exists in the traditional hash timelock method. Besides, this article uses the verifiable secret sharing method in the notary group, which can effectively prevent the centralization problem of the notary mechanism. Moreover, this article discusses the process of key processing, cross-chain transaction and transaction verification of the scheme, and designs the user credibility evaluation mechanism, which can effectively reduce the occurrence of malicious default of users. Compared with existing solutions, our solution has the advantage of effectively addressing time-out transaction attacks and centralization issues while guaranteeing security. The experiments also verify the effectiveness of the proposed scheme.

Dukun Adat sebagai Benteng Pendidikan Karakter Pemuda Desa Adat Tengger, Ngadas, Kabupaten Malang

This study aims to explore how the Tengger Indigenous community in Ngadas Village, Malang Regency, preserves their traditions amidst the challenges of modernization. The research employs a historical method, which includes four primary stages: (1) heuristic, involving the collection of data through books, journal articles, newspapers, as well as interviews and field observations; (2) verification, focusing on the credibility evaluation of sources by conducting source criticism; (3) interpretation, or the process of data interpretation; and (4) historiography, related to how the data is presented. The findings of this research highlight the crucial role of traditional healers as informal leaders who are responsible not only for religious rituals but also for addressing social issues in the community and educating the young generation with positive character values. The study concludes that traditional healers play a key role in integrating tradition with the changes of the times, and that the traditional farming practices of the Tengger community are not only their main source of livelihood but also a means to shield the community from the negative impacts of modernization.

Readability and credibility evaluation of most-visited health websites based on eBizMBA and Alexa global ranking

Introduction: Online health information is one of the most important and widely used sources of information. Currently, a significant number of individuals use the internet for health-related information to learn about health, disease, health promotion, and threats to their health.Material and Methods: This research examined the top 15 health websites based on their popularity in eBizMBA and Alexa rank from January to February 2022. A total of 30 health websites (15 from each category) were evaluated in terms of credibility by the use of Journal of the American Medical Association (JAMA) and health on the net foundation (HON) code. Also, the readability of the mentioned websites was evaluated by the use of four readability tools.Results: Most of the websites ranked by both Alexa and eBizMBA met the “Authority” and” Complementarity" criteria. When it comes to the readability of the 30 most visited health websites according to eBizMBA and Alexa analytics in the world, the analysis demonstrated that the readability of highly-ranked health websites was higher than the recommended level.Conclusion: Some of the websites had deficiencies according to the HONcode and JAMA criteria, and the average readability of the websites did not meet the gold standard. Despite the increasing use of the internet for medical information, these resources' poor quality and readability remain a barrier to informed decision-making of patients.