Information Bias Research Articles

Why Do Social Media Users Accept, Doubt or Resist Corrective Information? A Qualitative Analysis of Comments in Response to Corrective Information on Social Media

ABSTRACT Although the widespread application of corrective information has been found to lower the credibility of misinformation, there may be important sources of resistance among social media users that potentially limit the effectiveness of fact-checking, warning messages, and community-based verifications. Yet, to date, we lack an inductive and context-bound understanding of users’ responses to these different applications, and the reasons why users distrust or avoid corrections online. Against this backdrop, this paper relies on an in-depth qualitative content analysis of responses to different forms of corrective information on Facebook, Twitter, and TikTok. The study’s main findings inform a typology of resistance consisting of (1) expressing doubts on the selection biases of corrective information; (2) challenging the evidence and conclusions of corrective information; (3) blaming the correction for being biased and/or partisan and (4) labeling the correction or intervention as disinformation itself. The implications for journalism practice and content moderation are discussed.

Analysis Of Factors Related To Covid-19 Prevention Efforts Among Health Sciences College Students In Cirebon 2022

The negative information bias on social media can lead to a wrong perspective on COVID-19 cases and cause behavior in efforts to prevent COVID-19 to get worse, so that deaths continue to increase and continue to grow. Based on data from 231 countries that have confirmed COVID-19 with a total of 516,476,402 people and 6,258,023 people died, while in Indonesia, 6,049,541 people have recovered, and 5,887,786 have died and 156,424 have died. , while the confirmed cases of COVID-19 in West Java were 1,106,085, the cure rate was 1,089,648 and 15,795 died. The research method used is descriptive analytic research using a cross sectional research design. The subject of this research is STIKes Cirebon students with a population of 1286 students. The sampling technique used is disproportionate stratified random sampling, then takes the appropriate number of samples by simple random sampling to become respondents obtained a sample of 122 respondents, research instruments using questionnaires, data analysis using univariate, bivariate and multivariate analysis. The results showed that the relationship between frequency (p=0.043), duration (p=0.606), attention (p=0.038) and health literacy with COVID-19 prevention efforts (p=0.017). Attention variable is the most dominant variable with p value 0.026, OR value 2.787. There are 3 variables that are related and 1 variable that is not related to efforts to prevent COVID-19, where the most dominant variable is attention.

Opportunity abandonment: Why are entrepreneurs vulnerable to type I and II errors?

Opportunity actualization is a critical competency attributed to entrepreneurs, which has received widespread attention in the entrepreneurship literature. However, the knowledge of Entrepreneurial Opportunity Abandonment (EOA) decisions is limited. We, therefore, explore the relatively under-studied EOA, analyzing why entrepreneurs commit decision errors, abandon potentially viable opportunities (type I error) or pursue non-opportunity spaces (type II error), and ultimately forsake them later. Through a scoping literature review, we highlight more profound psychological variables that shape entrepreneurial opportunity behavior triggering EOA decisions. We discuss entrepreneurial cognitive limitations in articulating, concretizing, and communicating the opportunity. We argue that varying construal mindsets cause reification fallacies and create perceptual blocks in enunciating an opportunity idea. Further, subjective stakeholder feedback and biased information exchange largely shape EOA decisions, which are mediated through the information processing capacity of entrepreneurs. Finally, we propose four entrepreneurial decision-limiting hypotheses which require an empirical investigation.

A call for sex-positive epidemiology.

The World Health Organization specifies that sexual health requires the potential for pleasurable and safe sexual experiences. Yet epidemiologic research into sexual pleasure and other positive sexual outcomes has been scant. In this commentary, we aim to support the development and adoption of sex-positive epidemiology, which we define as epidemiology that incorporates the study of pleasure and other positive features alongside sexually transmitted infections and other familiar negative outcomes. We first call epidemiologists' attention to the potential role that stigma plays in the suppression of sex-positive research. We further describe existing measures of sex-positive constructs that may be useful in epidemiologic research. Finally, the study of sex-positive constructs is vulnerable to biases that are well-known to epidemiologists, especially selection bias, information bias, and confounding. We outline how these biases influence existing research and identify opportunities for future research. Epidemiologists have the potential to contribute a great deal to the study of sexuality by bringing their considerable methodological expertise to long-standing challenges in the field. We hope to encourage epidemiologists to broaden their sexual health research to encompass positive outcomes and pleasure.

Can you have it both ways? Attribution and plausible deniability in unclaimed coercion

Abstract States and non-state actors conduct unclaimed coercive attacks, inflicting costs on adversaries to signal resolve to prevail in a dispute while refraining from claiming or denying responsibility. Analysts argue that targets often know who is responsible, which enables coercive communication, and that the lack of claims of responsibility grants coercers plausible deniability in the eyes of third parties. The puzzle of different audiences holding different beliefs about who is behind an unclaimed attack, even when they may have the same information, has been neglected. We address this puzzle by theorising that targets and third parties tend to reach different conclusions due to distinct emotional reactions: targets are more likely to experience anger, which induces certainty and a desire to blame someone, as well as heuristic and biased information processing, prompting confident attribution despite the limited evidence. A vignette-based experiment depicting a terrorist attack lends empirical plausibility to our argument.

The contribution of sensory information asymmetry and bias of attribution to egocentric tendencies in effort comparison tasks.

When comparing themselves with others, people often evaluate their own behaviors more favorably. This egocentric tendency is often categorized as a bias of attribution, with favorable self-evaluation resulting from differing explanations of one's own behavior and that of others. However, studies on information availability in social contexts offer an alternative explanation, ascribing egocentric biases to the inherent informational asymmetries between performing an action and merely observing it. Since biases of attribution and availability often co-exist and interact with each other, it is not known whether they are both necessary for the egocentric biases to emerge. In this study, we used a design that allowed us to directly compare the contribution of these two distinct sources of bias to judgements about the difficulty of an effortful task. Participants exhibited no attribution bias as judgements made for themselves did not differ from those made for others. Importantly, however, participants perceived the tasks they actively performed to be harder than the tasks they observed, and this bias was magnified as the overall task difficulty increased. These findings suggest that information asymmetries inherent to the difference between actively performing a task and observing it can drive egocentric biases in effort evaluations on their own and without a contribution from biases of attribution.

A Study on Contributing Factors of IT Outsourcing Satisfaction Financial Service Industry in Hong Kong

This paper aims to identify the critical success factors in Hong Kong Financial Service Industry IT outsourcing satisfaction and propose possible satisfaction rate boosts. A hybrid methodology (qualitative and quantitative) was adopted to analyze the variables and their relationship thoroughly. The six members focus group was formed to discuss IT outsourcing, and the survey was conducted to collect 447 valid responses for data analysis. The six critical success factors were Perceived Information Security Risk, Quality of Service Provider, Contract Management, Internal Contract Experience, Communication and Regulatory Policy, identified to support satisfaction of Hong Kong FSI IT outsourcing after conducting the analysis. Three recommendations are proposed to improve IT outsourcing satisfaction based on the findings of critical success factors: (1) A Build-up of Vendor Evaluation Framework, (2) Enhancement for Knowledge Management, and (3) Enhance Performance Monitoring. The snowball sampling method might have introduced biased information. In future research, a more extensive research scale would be required to understand the whole population, which would be more appropriate for the industry to understand the need and construct any policy. This paper is a holistic approach to identifying factors that affect Hong Kong FSI IT outsourcing satisfaction. In addition, practical recommendations were proposed to improve those factors, thereby increasing the satisfaction rate of IT outsourcing.

AI ChatGPT and student engagement: Unraveling dimensions through PRISMA analysis for enhanced learning experiences

This PRISMA-based literature review aims to assess and analyze the measurement of student engagement dimensions within AI ChatGPT interactions. The central question is how to effectively evaluate these dimensions using established methods and leverage insights to enhance AI ChatGPT’s capacity to foster student engagement. The systematic review of PRISMA methodology identifies 16 relevant peer-reviewed research. All relevant and eligible research according to PRISMA methodology are analyzed to comprehend the intricacies of student engagement in AI ChatGPT interactions. The synthesis of these findings unveils the current state of knowledge on AI ChatGPT’s influence on student engagement and uncovers opportunities for future research. This review underscores AI ChatGPT’s potential as an educational tool, offering personalized experiences that bolster student engagement and learning outcomes. The systematic review established that, even though using ChatGPT has many advantages such as enhancing student engagement and academic involvement and supporting inquiry-based learning. However, there are some negative aspects such as lacking empathy and human emotions, limited contextual understanding, increased technology dependence and possibility of Inaccurate or Biased Information. In summary, this PRISMA-based review contributes to understanding the measurement of student engagement within AI ChatGPT. It identifies best practices, laying the foundation for further research and development. By optimizing AI ChatGPT’s effectiveness, educators and developers can craft more engaging and tailored learning experiences, ultimately enhancing educational outcomes.

Slimmable transformer with hybrid axial-attention for medical image segmentation

The transformer architecture has achieved remarkable success in medical image analysis owing to its powerful capability for capturing long-range dependencies. However, due to the lack of intrinsic inductive bias in modeling visual structural information, the transformer generally requires a large-scale pre-training schedule, limiting the clinical applications over expensive small-scale medical data. To this end, we propose a slimmable transformer to explore intrinsic inductive bias via position information for medical image segmentation. Specifically, we empirically investigate how different position encoding strategies affect the prediction quality of the region of interest (ROI) and observe that ROIs are sensitive to different position encoding strategies. Motivated by this, we present a novel Hybrid Axial-Attention (HAA) that can be equipped with pixel-level spatial structure and relative position information as inductive bias. Moreover, we introduce a gating mechanism to achieve efficient feature selection and further improve the representation quality over small-scale datasets. Experiments on LGG and COVID-19 datasets prove the superiority of our method over the baseline and previous works. Internal workflow visualization with interpretability is conducted to validate our success better; the proposed slimmable transformer has the potential to be further developed into a visual software tool for improving computer-aided lesion diagnosis and treatment planning.

Functional gastrointestinal disorders, quality of life, and behaviour in adolescents with history of infant colic.

To assess the prevalence of functional gastrointestinal disorders (FGIDs), health-related quality of life (HRQOL), and behavioural problems in a cohort of adolescents with a history of infant colic (IC), as defined by Wessel's criteria. 388 adolescents, aged 15-18 years, who participated in a randomised controlled trial for infants with colic, were invited for our observational follow-up study. Prevalence of FGIDs was assessed with the Rome IV Questionnaire on Paediatric Gastrointestinal Disorders (RIV-QPGD), HRQOL through self-report of the Paediatric Quality of Life Inventory (PedsQL), and behavioural problems through parent-report of the child behaviour checklist (CBCL). Multivariable models were used to compare prevalence rates of FGIDs and HRQOL scores. 190 (49%) adolescents with a history of IC (cases) and 381 controls were included (median age 17.0 [IQR 16.0-17.0] and 16.0 [15.0-17.0] years, respectively). Cases had a significantly higher risk for postprandial distress syndrome compared to controls (aOR 2.49 (95%CI 1.18-5.25), p = 0.002). After multivariable regression, total, physical and school HRQOL scores were significantly lower in cases compared to controls (p = 0.003, 0.001, and 0.009). Adolescents with a history of IC demonstrate higher prevalence rates of postprandial distress syndrome compared to controls. However, conclusions should be made with caution due to attrition and information bias.

Long-term trajectories of depressive symptoms in deployed military personnel: A 10-year prospective study

BackgroundMilitary missions, especially those involving combat exposure, are associated with an increased risk of depression. Understanding the long-term course of depressive symptoms post-deployment is important to improve decision-making regarding deployment and mental health policies in the military. This study investigates trajectories of depressive symptoms in the Dutch army, exploring the influence of factors such as demographics, early-life trauma, posttraumatic stress disorder (PTSD) symptoms, and deployment stressors. MethodsA cohort of 1032 military men and women deployed to Afghanistan (2005–2008) was studied from pre- to 10 years post-deployment. Depressive and PTSD symptoms were assessed using the Symptom CheckList-90 and the Self-Rating Inventory for PTSD. Demographics, early trauma, and deployment experiences were collected at baseline and after deployment, respectively. Latent Class Growth Analysis was used to explore heterogeneity in trajectories of depressive symptoms over time. ResultsFour trajectories were found: resilient (65%), intermediate-stable (20%), symptomatic-chronic (9%), and late-onset-increasing (6%). The resilient group experienced fewer deployment stressors, while the symptomatic-chronic group reported more early life traumas. Trajectories with elevated depressive symptoms consistently demonstrated higher PTSD symptoms. LimitationsPotential nonresponse bias and missing information due to the longitudinal design and extensive follow-up times. ConclusionsThis study identified multiple trajectories of depressive symptoms in military personnel up to 10 years post-deployment, associated with early trauma, deployment stressors, adverse life events and PTSD symptoms. The prevalence of the resilient trajectory suggests a substantial level of resilience among deployed military personnel. These findings provide valuable insights and a foundation for further research.

Migrate demographic group for fair Graph Neural Networks

Graph Neural networks (GNNs) have been applied in many scenarios due to the superior performance of graph learning. However, fairness is always ignored when designing GNNs. As a consequence, biased information in training data can easily affect vanilla GNNs, causing biased results toward particular demographic groups (divided by sensitive attributes, such as race and age). There have been efforts to address the fairness issue. However, existing fair techniques generally divide the demographic groups by raw sensitive attributes and assume that are fixed. The biased information correlated with raw sensitive attributes will run through the training process regardless of the implemented fair techniques. It is urgent to resolve this problem for training fair GNNs. To tackle this problem, we propose a brand new framework, FairMigration, which is able to migrate the demographic groups dynamically, instead of keeping that fixed with raw sensitive attributes. FairMigration is composed of two training stages. In the first stage, the GNNs are initially optimized by personalized self-supervised learning, and the demographic groups are adjusted dynamically. In the second stage, the new demographic groups are frozen and supervised learning is carried out under the constraints of new demographic groups and adversarial training. Extensive experiments reveal that FairMigration achieves a high trade-off between model performance and fairness.

Enhanced EMC-Advantages of partially known orientations in x-ray single particle imaging.

Single particle imaging of proteins in the gas phase with x-ray free-electron lasers holds great potential to study fast protein dynamics, but is currently limited by weak and noisy data. A further challenge is to discover the proteins' orientation as each protein is randomly oriented when exposed to x-rays. Algorithms such as the expand, maximize, and compress (EMC) exist that can solve the orientation problem and reconstruct the three-dimensional diffraction intensity space, given sufficient measurements. If information about orientation were known, for example, by using an electric field to orient the particles, the reconstruction would benefit and potentially reach better results. We used simulated diffraction experiments to test how the reconstructions from EMC improve with particles' orientation to a preferred axis. Our reconstructions converged to correct maps of the three-dimensional diffraction space with fewer measurements if biased orientation information was considered. Even for a moderate bias, there was still significant improvement. Biased orientations also substantially improved the results in the case of missing central information, in particular in the case of small datasets. The effects were even more significant when adding a background with 50% the strength of the averaged diffraction signal photons to the diffraction patterns, sometimes reducing the data requirement for convergence by a factor of 10. This demonstrates the usefulness of having biased orientation information in single particle imaging experiments, even for a weaker bias than what was previously known. This could be a key component in overcoming the problems with background noise that currently plague these experiments.

How ‘going online’ mediates the challenges of policy elite interviews

Relevant data on sensitive and politicised political processes might be difficult to obtain and is sometimes even purposely hidden from the public domain. Policy elite interviews constitute crucial sources of information in policy research. However, there are significant challenges associated with ‘researching up’ which sets elite interviews apart from other interview methods. Although there is a great deal of literature concerning interviews conducted via phone or audio-visual computer programs, the implications of conducting policy elite interviews online have received surprisingly little attention. This paper discusses how going online can mediate the main challenges associated with policy elite interviews. These challenges include barriers to gaining access, dealing with biased information, and problems concerning positionality. Based on a least likely case to access relevant data, this paper reflects on personal experience from 20 online interviews with European Commission representatives on policy responses to the 2015 migration crisis. The paper concludes that the online format facilitated unique insights into a highly controversial issue area.

Value chain microfinance

Abstract We study the provision of financial services to small firms, consumers, and workers in developing countries as part of value chain relationships: value chain microfinance (VCMF). We first explore how VCMF can both overcome barriers to financial access—including asymmetric information, enforcement, and behavioural biases—and strengthen value chains, but also how it can introduce new challenges. We then review a recent empirical literature at the intersection of value chains and microfinance, studying the demand for and effects of VCMF in credit, insurance, and savings markets. We conclude by highlighting promising directions for future work.

Multispectral image defogging based on a wavelength-dependent extinction coefficient model in fog.

Most of the state-of-the-art defogging models presented in the literature assume that the attenuation coefficient of all spectral channels is constant, which inevitably leads to spectral distortion and information bias. To address this issue, this paper proposes a defogging method that takes into account the difference between the extinction coefficients of multispectral channels of light traveling through fog. Then the spatially distributed transmission map of each spectral channel is reconstructed to restore the fog-degraded images. The experimental results of various realistic complex scenes show that the proposed method has more outstanding advantages in restoring lost detail, compensating for degraded spectral information, and recognizing more targets hidden in uniform ground fog than state-of-the-art technologies. In addition, this work provides a method to characterize the intrinsic property of fog expressed as multispectral relative extinction coefficients, which act as a fundament for further reconstruction of multispectral information.

A theory of the neural mechanisms underlying negative cognitive bias in major depression.

The widely acknowledged cognitive theory of depression, developed by Aaron Beck, focused on biased information processing that emphasizes the negative aspects of affective and conceptual information. Current attempts to discover the neurological mechanism underlying such cognitive and affective bias have successfully identified various brain regions associated with severally biased functions such as emotion, attention, rumination, and inhibition control. However, the neurobiological mechanisms of how individuals in depression develop this selective processing toward negative is still under question. This paper introduces a neurological framework centered around the frontal-limbic circuit, specifically analyzing and synthesizing the activity and functional connectivity within the amygdala, hippocampus, and medial prefrontal cortex. Firstly, a possible explanation of how the positive feedback loop contributes to the persistent hyperactivity of the amygdala in depression at an automatic level is established. Building upon this, two hypotheses are presented: hypothesis 1 revolves around the bidirectional amygdalohippocampal projection facilitating the amplification of negative emotions and memories while concurrently contributing to the impediment of the retrieval of opposing information in the hippocampus attractor network. Hypothesis 2 highlights the involvement of the ventromedial prefrontal cortex in the establishment of a negative cognitive framework through the generalization of conceptual and emotional information in conjunction with the amygdala and hippocampus. The primary objective of this study is to improve and complement existing pathological models of depression, pushing the frontiers of current understanding in neuroscience of affective disorders, and eventually contributing to successful recovery from the debilitating affective disorders.

The bidirectional temporal relationship between parenting stress and child maltreatment: A cross-lagged study based on intervention and cohort data

BackgroundParenting stress has long been proposed as a major risk factor for child maltreatment. However, there is a lack of evidence from existing studies on the temporal sequence to establish a causal relationship. This study aims to examine bidirectional temporal relationships between parenting stress and child maltreatment. MethodsLongitudinal data from two different sources were analysed: a pre-post study of an online parenting programme conducted across six countries - the ePLH Evaluation Study, and a prospective cohort study in the United States - LONGSCAN. Cross-lagged panel model on parenting stress and child maltreatment was used in each dataset. ResultsBased on repeatedly measured data of 484 caregivers in the ePLH study across five time points (every two weeks), we found that parenting stress at an earlier time point predicted later child maltreatment (IRR = 1.14, 95 % CI: 1.10,1.18). In addition, the occurrence of child maltreatment was associated with higher subsequent short-term parenting stress (IRR = 1.04, 95 % CI: 1.01,1.08) and thus could form a vicious circle. In the LONGSCAN analysis with 772 caregivers who were followed up from child age of 6 to child age of 16, we also found parenting stress at an earlier time point predicted later child maltreatment (β = 0.11, 95 % CI: 0.01,0.20), but did not observe an association between child maltreatment and subsequent long-term parenting stress. LimitationsPotential information bias on the measurements. ConclusionsThis study provides evidence for a bidirectional temporal relationship between parenting stress and child maltreatment, which should be considered in parenting intervention programmes.

Incomplete Multiview Clustering via Semidiscrete Optimal Transport for Multimedia Data Mining in IoT

With the wide deployment of the Internet of Things (IoT), large volumes of incomplete multiview data that violates data integrity is generated by various applications, which inevitably produces negative impacts on the quality of service of IoT systems. Incomplete multiview clustering (IMC), as an essential technique of data processing, has the potential for mining patterns of incomplete IoT data. However, previous methods utilize notion-strong distances that can only measure differences between distributions at the overlap of data manifolds in fusing complementary information of data for pattern mining. They may suffer from biased estimation and information loss in capturing intrinsic structures of incomplete multiview data. To address these challenges, a semidiscrete multiview optimal transport (SD-MOT) is defined for IMC, which utilizes distances with weak notions to capture intrinsic structures of incomplete multiview data. Specifically, IMC is recast as an equivalent optimal transport between continuous incomplete multiview data and discrete clustering centroids, to avoid the strict assumption on overlap between manifolds in pattern mining. Then, SD-MOT is instantiated as a deep incomplete contrastive clustering network to remedy biased estimation and information loss on intrinsic structures of incomplete multiview data. Afterwards, a variational solution to SD-MOT is derived to effectively train the network parameters for pattern mining. Finally, extensive experiments on four representative incomplete multiview datasets verify the superiority of SD-MOT in comparison with nine baseline methods.

An experimental test of whether financial incentives constitute undue inducement in decision-making

Around the world, laws limit the incentives that can be paid for transactions such as human research participation, egg donation or gestational surrogacy. A key reason is concerns about ‘undue inducement’—the influential but empirically untested hypothesis that incentives can cause harm by distorting individual decision-making. Here I present two experiments (n = 671 and n = 406), including one based on a highly visceral transaction (eating insects). Incentives caused biased information search—participants offered a higher incentive to comply more often sought encouragement to do so. However, I demonstrate theoretically that such behaviour does not prove that incentives have harmful effects; it is consistent with Bayesian rationality. Empirically, although a substantial minority of participants made bad decisions, incentives did not magnify them in a way that would suggest allowing a transaction but capping incentives. Under the conditions of this experiment, there was no evidence that higher incentives could undermine welfare for transactions that are permissible at low incentives.