Showing papers on "Credibility published in 2020"

Celebrity vs. Influencer endorsements in advertising: the role of identification, credibility, and Product-Endorser fit

Abstract: In their marketing efforts, companies increasingly abandon traditional celebrity endorsers in favor of social media influencers, such as vloggers and Instafamous personalities. The effectiveness of...

Development of the Instrument to assess the Credibility of Effect Modification Analyses (ICEMAN) in randomized controlled trials and meta-analyses.

Abstract: BACKGROUND: Most randomized controlled trials (RCTs) and meta-analyses of RCTs examine effect modification (also called a subgroup effect or interaction), in which the effect of an intervention varies by another variable (e.g., age or disease severity). Assessing the credibility of an apparent effect modification presents challenges; therefore, we developed the Instrument for assessing the Credibility of Effect Modification Analyses (ICEMAN). METHODS: To develop ICEMAN, we established a detailed concept; identified candidate credibility considerations in a systematic survey of the literature; together with experts, performed a consensus study to identify key considerations and develop them into instrument items; and refined the instrument based on feedback from trial investigators, systematic review authors and journal editors, who applied drafts of ICEMAN to published claims of effect modification. RESULTS: The final instrument consists of a set of preliminary considerations, core questions (5 for RCTs, 8 for meta-analyses) with 4 response options, 1 optional item for additional considerations and a rating of credibility on a visual analogue scale ranging from very low to high. An accompanying manual provides rationales, detailed instructions and examples from the literature. Seventeen potential users tested ICEMAN; their suggestions improved the user-friendliness of the instrument. INTERPRETATION: The Instrument for assessing the Credibility of Effect Modification Analyses offers explicit guidance for investigators, systematic reviewers, journal editors and others considering making a claim of effect modification or interpreting a claim made by others.

The effect of electronic word of mouth communications on intention to buy: A meta-analysis

Abstract: The aim of this research is to synthesise findings from previous studies by employing weight and meta-analysis to reconcile conflicting evidence and draw a “big picture” of eWOM factors influencing consumers’ intention to buy. By using the findings from 69 studies, this research identified best (e.g. argument quality, valence, eWOM usefulness, trust in message), promising (e.g. eWOM credibility, emotional trust, attitude towards website) and least effective (e.g. volume, existing eWOM, source credibility) predictors of intention to buy in eWOM research. Additionally, the effect size of each predictor was calculated by performing meta-analysis. For academics, understanding what influences consumers’ intention to buy will help set the agenda for future research directions; for practitioners, it will provide benefit in terms of practical guidance based on detailed analysis of specific factors influencing consumers’ intention to buy, which could enhance their marketing activities.

‘You really are a great big sister’ – parasocial relationships, credibility, and the moderating role of audience comments in influencer marketing

Abstract: This study examines the moderating role of audience comments in influencer marketing. A YouTube vlog entry by a social media influencer featuring the endorsement of a brand was studied, and an expe...

Cognitive Dissonance or Credibility? A Comparison of Two Theoretical Explanations for Selective Exposure to Partisan News

Abstract: Selective exposure research indicates that news consumers tend to seek out attitude-consistent information and avoid attitude-challenging information. This study examines online news credibility and cognitive dissonance as theoretical explanations for partisan selective exposure behavior. After viewing an attitudinally consistent, challenging, or politically balanced online news source, cognitive dissonance, credibility perceptions, and likelihood of selective exposure were measured. Results showed that people judge attitude-consistent and neutral news sources as more credible than attitude-challenging news sources, and although people experience slightly more cognitive dissonance when exposed to attitude-challenging news sources, overall dissonance levels were quite low. These results refute the cognitive dissonance explanation for selective exposure and suggest a new explanation that is based on credibility perceptions rather than psychological discomfort with attitude-challenging information.

Lies Kill, Facts Save: Detecting COVID-19 Misinformation in Twitter

Abstract: Online social networks (ONSs) such as Twitter have grown to be very useful tools for the dissemination of information. However, they have also become a fertile ground for the spread of false information, particularly regarding the ongoing coronavirus disease 2019 (COVID-19) pandemic. Best described as an infodemic, there is a great need, now more than ever, for scientific fact-checking and misinformation detection regarding the dangers posed by these tools with regards to COVID-19. In this article, we analyze the credibility of information shared on Twitter pertaining the COVID-19 pandemic. For our analysis, we propose an ensemble-learning-based framework for verifying the credibility of a vast number of tweets. In particular, we carry out analyses of a large dataset of tweets conveying information regarding COVID-19. In our approach, we classify the information into two categories: credible or non-credible. Our classifications of tweet credibility are based on various features, including tweet- and user-level features. We conduct multiple experiments on the collected and labeled dataset. The results obtained with the proposed framework reveal high accuracy in detecting credible and non-credible tweets containing COVID-19 information.

Evaluating the credibility of anchor based estimates of minimal important differences for patient reported outcomes: instrument development and reliability study.

Abstract: Objective To develop an instrument to evaluate the credibility of anchor based minimal important differences (MIDs) for outcome measures reported by patients, and to assess the reliability of the instrument. Design Instrument development and reliability study. Data sources Initial criteria were developed for evaluating the credibility of anchor based MIDs based on a literature review (Medline, Embase, CINAHL, and PsycInfo databases) and the experience of the authors in the methodology for estimation of MIDs. Iterative discussions by the team and pilot testing with experts and potential users facilitated the development of the final instrument. Participants With the newly developed instrument, pairs of masters, doctoral, or postdoctoral students with a background in health research methodology independently evaluated the credibility of a sample of MID estimates. Main outcome measures Core credibility criteria applicable to all anchor types, additional criteria for transition rating anchors, and inter-rater reliability coefficients were determined. Results The credibility instrument has five core criteria: the anchor is rated by the patient; the anchor is interpretable and relevant to the patient; the MID estimate is precise; the correlation between the anchor and the outcome measure reported by the patient is satisfactory; and the authors select a threshold on the anchor that reflects a small but important difference. The additional criteria for transition rating anchors are: the time elapsed between baseline and follow-up measurement for estimation of the MID is optimal; and the correlations of the transition rating with the baseline, follow-up, and change score in the patient reported outcome measures are satisfactory. Inter-rater reliability coefficients (ĸ) for the core criteria and for one item from the additional criteria ranged from 0.70 to 0.94. Reporting issues prevented the evaluation of the reliability of the three other additional criteria for the transition rating anchors. Conclusions Researchers, clinicians, and healthcare policy decision makers can consider using this instrument to evaluate the design, conduct, and analysis of studies estimating anchor based minimal important differences.

Talking about CSR matters: employees’ perception of and reaction to their company’s CSR communication in four different CSR domains

Abstract: Drawing on signaling and social identity theories, we analyze how liking of the company’s CSR advertisements, message credibility, and cause-company fit influence employees’ evaluation of t...

ReCOVery: A Multimodal Repository for COVID-19 News Credibility Research

Abstract: First identified in Wuhan, China, in December 2019, the outbreak of COVID-19 has been declared as a global emergency in January, and a pandemic in March 2020 by the World Health Organization (WHO) Along with this pandemic, we are also experiencing an "infodemic" of information with low credibility such as fake news and conspiracies In this work, we present ReCOVery, a repository designed and constructed to facilitate research on combating such information regarding COVID-19 We first broadly search and investigate ~2,000 news publishers, from which 60 are identified with extreme [high or low] levels of credibility By inheriting the credibility of the media on which they were published, a total of 2,029 news articles on coronavirus, published from January to May 2020, are collected in the repository, along with 140,820 tweets that reveal how these news articles have spread on the Twitter social network The repository provides multimodal information of news articles on coronavirus, including textual, visual, temporal, and network information The way that news credibility is obtained allows a trade-off between dataset scalability and label accuracy Extensive experiments are conducted to present data statistics and distributions, as well as to provide baseline performances for predicting news credibility so that future methods can be compared Our repository is available at this http URL

Fighting fake news in the COVID-19 era: policy insights from an equilibrium model.

Abstract: The COVID-19 crisis has revealed structural failures in governance and coordination on a global scale. With related policy interventions dependent on verifiable evidence, pandemics require governments to not only consider the input of experts but also ensure that science is translated for public understanding. However, misinformation and fake news, including content shared through social media, compromise the efficacy of evidence-based policy interventions and undermine the credibility of scientific expertise with potentially longer-term consequences. We introduce a formal mathematical model to understand factors influencing the behavior of social media users when encountering fake news. The model illustrates that direct efforts by social media platforms and governments, along with informal pressure from social networks, can reduce the likelihood that users who encounter fake news embrace and further circulate it. This study has implications at a practical level for crisis response in politically fractious settings and at a theoretical level for research about post-truth and the construction of fact.

Use of Quasi-Experimental Research Designs in Education Research: Growth, Promise, and Challenges:

Abstract: In the past few decades, we have seen a rapid proliferation in the use of quasi-experimental research designs in education research. This trend, stemming in part from the “credibility revolution” i...

ReCOVery: A Multimodal Repository for COVID-19 News Credibility Research

Abstract: First identified in Wuhan, China, in December 2019, the outbreak of COVID-19 has been declared as a global emergency in January, and a pandemic in March 2020 by the World Health Organization (WHO). Along with this pandemic, we are also experiencing an "infodemic" of information with low credibility such as fake news and conspiracies. In this work, we present ReCOVery, a repository designed and constructed to facilitate research on combating such information regarding COVID-19. We first broadly search and investigate ~2,000 news publishers, from which 60 are identified with extreme [high or low] levels of credibility. By inheriting the credibility of the media on which they were published, a total of 2,029 news articles on coronavirus, published from January to May 2020, are collected in the repository, along with 140,820 tweets that reveal how these news articles have spread on the Twitter social network. The repository provides multimodal information of news articles on coronavirus, including textual, visual, temporal, and network information. The way that news credibility is obtained allows a trade-off between dataset scalability and label accuracy. Extensive experiments are conducted to present data statistics and distributions, as well as to provide baseline performances for predicting news credibility so that future methods can be compared. Our repository is available at http://coronavirus-fakenews.com.

Reconceptualizing nature-of-science education in the age of social media

Abstract: Correspondence D i et mar H öt t ec ke, F ac ul t y of Educ at i on, P hy si c s Educ at i on G r oup, U ni v er si t y of H ambur g, 20146 H ambur g, G er many . Emai l : di et mar . hoet t ec ke@ uni hambur g. de Abstract Individuals are increasingly relying on social media as their primary source of scientific information. Science education needs to adapt. Nature of science (NOS) education is already widely accept ed as essential to scientific literacy and to an informed public. We argue that NOS now needs to also include the NOS communication: its mediation, mechanisms, and manipulation. Namely, students need to learn about the epistemics of communicative practices, both within science (as a model) and in society. After profiling the current media landscape, we consider the implications of recent major studies on science communication for science education in the 21st century. We focus in particular on communicative patterns prominent in social media: algorithms to aggregate news, filter bubbles, echo chambers, spirals of silence, false‐ consensus effects, fake news, and intentional disinformation. We claim that media literacy is now essential to a complete view of the NOS, or “ Whole Science.” We portray that new content as a n extension of viewing science as a system of specialized experts, with mutual epistemic dependence, and the social and communicative practices that establish trust and credibility.

The Trustworthiness of Content Analysis

Abstract: This chapter aims to present criteria for trustworthiness. Qualitative researchers commonly have different opinions about which criteria are the best for evaluating trustworthiness. However, the current consensus is that credibility, transferability, dependability, confirmability, and authenticity are the five most relevant terms for determining the trustworthiness of research. This chapter will explain what each of these criteria mean, and will demonstrate how they can be applied to research that includes content analysis. Briefly, credibility can be defined as confidence in the ‘truth’ of the findings. Transferability means that the findings are also applicable in other contexts, while dependability indicates that the findings are consistent and could be replicated. Confirmability describes the degree of neutrality or, in other words, the extent to which the findings of a study reflect the respondents’ opinions and experiences rather than the researchers’ biases, motivations, or interests. Authenticity is concerned with the ability of researchers to accurately depict the diverse realities that exist in the data collected from participants.

Is TripAdvisor still relevant? The influence of review credibility, review usefulness, and ease of use on consumers’ continuance intention

Abstract: Recent figures show that users are discontinuing their usage of TripAdvisor, the leading user-generated content (UGC) platform in the tourism sector. Hence, it is relevant to study the factors that influence travelers’ continued use of TripAdvisor.,The authors have integrated constructs from the technology acceptance model, information systems (IS) continuance model and electronic word of mouth literature. They used PLS-SEM (smartPLS V.3.2.8) to test the hypotheses using data from 297 users of TripAdvisor recruited through Prolific.,Findings reveal that perceived ease of use, online consumer review (OCR) credibility and OCR usefulness have a positive impact on customer satisfaction, which ultimately leads to continuance intention of UGC platforms. Customer satisfaction mediates the effect of the independent variables on continuance intention.,Managers of UGC platforms (i.e. TripAdvisor) can benefit from the findings of this study. Specifically, they should improve the ease of use of their platforms by facilitating travelers’ information searches. Moreover, they should use signals to make credible and helpful content stand out from the crowd of reviews.,This is the first study that adopts the IS continuance model in the travel and tourism literature to research the factors influencing consumers’ continued use of travel-based UGC platforms. Moreover, the authors have extended this model by including new constructs that are particularly relevant to UGC platforms, such as performance heuristics and OCR credibility.

Influencer marketing on Instagram: How sponsorship disclosure, influencer credibility, and brand credibility impact the effectiveness of Instagram promotional post

Abstract: Despite the increasing interest in celebrity influencers as a marketing communication tool, much remains to be explored to understand how influencer credibility combined with brand credibility affe...

Evaluating Sources of Scientific Evidence and Claims in the Post-Truth Era May Require Reappraising Plausibility Judgments.

Abstract: When individuals have questions about scientific issues, they often search the Internet. Evaluating sources of information and claims they find has become more difficult in the post-truth era. Stud...

Evidence combination based on prospect theory for multi-sensor data fusion.

Abstract: Multi-sensor data fusion (MSDF) is an efficient technology to enhance the performance of the system with the involvement of different kinds of sensors, which are broadly utilized in many fields at present. However, the data obtained from multi-sensors may have different degrees of uncertainty in the practical applications. Evidence theory is very useful to convey and manage uncertainty without a priori probability, so that it has been proverbially adopted in the information fusion fields. However, in the face of conflicting evidences, it has the possibility of producing counterintuitive results via conducting the Dempster's combination rule (DCR). To solve the above-mentioned issue, a hybrid MSDF method is exploited through integrating a newly defined evidential credibility measure of evidences based on prospect theory and the evidence theory. More specifically, a series of concepts for the evidential credibility measure are first presented, including the local credibility degree, global credibility degree, evidential credibility estimation and credibility prospect value function to comprehensively describe the award and punish grades in terms of credible evidence and incredible evidence, respectively. Based on the above researches, an appropriate weight for each evidence can be obtained. Ultimately, the weight of each evidence is leveraged to amend the primitive evidences before conducting DCR. The results attained in the experiments demonstrate that the hybrid MSDF approach is efficient and superior to handle conflict evidences as well as the application in data fusion problems.

Effects of Credibility Indicators on Social Media News Sharing Intent

Abstract: In recent years, social media services have been leveraged to spread fake news stories. Helping people spot fake stories by marking them with credibility indicators could dissuade them from sharing such stories, thus reducing their amplification. We carried out an online study (N = 1,512) to explore the impact of four types of credibility indicators on people's intent to share news headlines with their friends on social media. We confirmed that credibility indicators can indeed decrease the propensity to share fake news. However, the impact of the indicators varied, with fact checking services being the most effective. We further found notable differences in responses to the indicators based on demographic and personal characteristics and social media usage frequency. Our findings have important implications for curbing the spread of misinformation via social media platforms.

Public Oversight and Reporting Credibility: Evidence from the PCAOB Audit Inspection Regime

Abstract: This paper studies the impact of public audit oversight on financial reporting credibility. We analyze changes in market responses to earnings news after public audit oversight is introduced, exploiting that the regime onset depends on fiscal year-ends, auditors, and the rollout of auditor inspections. We find that investors respond more strongly to earnings news following public audit oversight. Corroborating these findings, we find an increase in volume responses to 10-K filings after the new regime. Our results show that public audit oversight can enhance reporting credibility and that this credibility is priced in capital markets.Authors have furnished an Internet Appendix, which is available on the Oxford UniversityPress Web site next to the link to the final published paper online.

Corporate Governance, Integrated Reporting and the Use of Credibility-enhancing Mechanisms on Integrated Reports

Abstract: The International Integrated Reporting Council (IIRC) and the South African King III Report on Governance emphasize the role of corporate governance in preparing a high-quality integrated report an...

Consideration of a Credibility Assessment Framework in Model-Informed Drug Development: Potential Application to Physiologically-Based Pharmacokinetic Modeling and Simulation.

Abstract: The use of computational models in drug development has grown during the past decade. These model-informed drug development (MIDD) approaches can inform a variety of drug development and regulatory decisions. When used for regulatory decision making, it is important to establish that the model is credible for its intended use. Currently, there is no consensus on how to establish and assess model credibility, including the selection of appropriate verification and validation activities. In this article, we apply a risk-informed credibility assessment framework to physiologically-based pharmacokinetic modeling and simulation and hypothesize this evidentiary framework may also be useful for evaluating other MIDD approaches. We seek to stimulate a scientific discussion around this framework as a potential starting point for uniform assessment of model credibility across MIDD. Ultimately, an overarching framework may help to standardize regulatory evaluation across therapeutic products (i.e., drugs and medical devices).

All the News That’s Fit to Fabricate: AI-Generated Text as a Tool of Media Misinformation

Abstract: Online misinformation has become a constant; only the way actors create and distribute that information is changing. Advances in artificial intelligence (AI) mean that actors can now synthetically generate text in ways that mimic the style and substance of human-created news stories. We carried out three original experiments to study whether these AI-generated texts are credible and can influence opinions on foreign policy — a likely target of real-world misinformation. The first evaluated human detection of AI-generated text relative to the original story from which it was generated. The second examined the credibility distribution across different model sizes to gauge whether improvements in processing produce commensurate increases in credibility. The third investigated the interaction between partisanship and AI-generated news. We find that individuals are largely incapable of distinguishing between AI and human-generated text; partisanship affects the perceived credibility of the story; and exposure to the text does little to change individuals’ policy views. The findings have important implications for the way malicious actors might employ AI in online misinformation campaigns and electoral interference.

Credibility Perceptions and Detection Accuracy of Fake News Headlines on Social Media: Effects of Truth-Bias and Endorsement Cues:

Abstract: This article focuses on message credibility and detection accuracy of fake and real news as represented on social media. We developed a deception detection paradigm for news headlines and conducted...

Russian Twitter Accounts and the Partisan Polarization of Vaccine Discourse, 2015-2017.

Abstract: Objectives. To understand how Twitter accounts operated by the Russian Internet Research Agency (IRA) discussed vaccines to increase the credibility of their manufactured personas.Methods. We analy...

Signalling Effects of Vlogger Popularity on Online Consumers

Abstract: This article investigates the effect of video loggers (vloggers) popularity on consumer credibility perception and purchase intention. It employs a two (high versus low vlogger popularity) by two (...