Dynamic source credibility and its impacts on knowledge revision.

Corrections to readers' misconceptions should result in higher belief when information sources are of high credibility. However, evaluations of credibility may be malleable, and we do not yet fully understand how changes to a source's credibility influence readers' credibility evaluations and knowledge revision outcomes. Thus, in two experiments, we examined how updating a source's credibility (Experiment 1: initially neutral sources later updated to be high-, low-, or neutral-credibility sources; Experiment 2: initially high- or low-credibility sources later updated to be low- or high-credibility sources) influenced knowledge revision and source credibility evaluations after readers engaged with refutation and non-refutation texts. Results showed that readers revised their credibility judgments from neutral-, high-, and low-credibility initial evaluations, indicating that source judgments are malleable rather than fixed. In addition, refutations from sources that are later revealed to be of high credibility can facilitate revision of both knowledge and initial source credibility evaluations.

The nature of misinformation in education.

In this opinion piece, we review and characterize the nature of misinformation in education and discuss the implications for corrective efforts. In education, misinformation manifests at three different levels: the individual, the community, and the system. At the individual level, misinformation manifests as naive beliefs or misconceptions students hold before they receive instruction or because of instruction. At the community level, misinformation manifests as shared flawed views or misconceptions about certain topics often around risk factors and treatments of learning disabilities. At the system level, misinformation manifests as state or district educational policies and practices that have no scientific evidence. Thus, corrective efforts in education must be implemented at all three levels and follow best practices.

Preventing online disinformation propagation: Cost-effective dynamic budget allocation of refutation, media censorship, and social bot detection.

Disinformation refers to false rumors deliberately fabricated for certain political or economic conspiracies. So far, how to prevent online disinformation propagation is still a severe challenge. Refutation, media censorship, and social bot detection are three popular approaches to stopping disinformation, which aim to clarify facts, intercept the spread of existing disinformation, and quarantine the source of disinformation, respectively. In this paper, we study the collaboration of the above three countermeasures in defending disinformation. Specifically, considering an online social network, we study the most cost-effective dynamic budget allocation (DBA) strategy for the three methods to minimize the proportion of disinformation-supportive accounts on the network with the lowest expenditure. For convenience, we refer to the search for the optimal DBA strategy as the DBA problem. Our contributions are as follows. First, we propose a disinformation propagation model to characterize the effects of different DBA strategies on curbing disinformation. On this basis, we establish a trade-off model for DBA strategies and reduce the DBA problem to an optimal control model. Second, we derive an optimality system for the optimal control model and develop a heuristic numerical algorithm called the DBA algorithm to solve the optimality system. With the DBA algorithm, we can find possible optimal DBA strategies. Third, through numerical experiments, we estimate key model parameters, examine the obtained DBA strategy, and verify the effectiveness of the DBA algorithm. Results show that the DBA algorithm is effective.

Configurational patterns for COVID-19 related social media rumor refutation effectiveness enhancement based on machine learning and fsQCA.

Infodemics are intertwined with the COVID-19 pandemic, affecting people's perception and social order. To curb the spread of COVID-19 related false rumors, fuzzy-set qualitative comparative analysis (fsQCA) is used to find configurational pathways to enhance rumor refutation effectiveness. In this paper, a total of 1,903 COVID-19 related false rumor refutation microblogs on Sina Weibo are collected by a web crawler from January 1, 2022 to April 20, 2022, and 10 main conditions affecting rumor refutation effectiveness index (REI) are identified based on "three rules of epidemics". To reduce data redundancy, five ensemble machine learning models are established and tuned, among which Light Gradient Boosting Machine (LGBM) regression model has the best performance. Then five core conditions are extracted by feature importance ranking of LGBM. Based on fsQCA with the five core conditions, REI enhancement can be achieved through three different pathway elements configurations solutions: "Highly influential microblogger * high followers' stickiness microblogger", "high followers' stickiness microblogger * highly active microblogger * concise information description" and "high followers' stickiness microblogger * the sentiment tendency of the topic * concise information description". Finally, decision-making suggestions for false rumor refutation platforms and new ideas for improving false rumor refutation effectiveness are proposed. The innovation of this paper reflects in exploring the REI enhancement strategy from the perspective of configuration for the first time.

The 'Fauci Effect': Reducing COVID-19 misconceptions and vaccine hesitancy using an authentic multimodal intervention.

Social media environments enable users to proliferate misinformation surrounding COVID-19. Expert sources, such as Dr. Anthony Fauci have leveraged social media to present corrective multimedia messages. However, little is known about the efficacy of these messages in revising common misconceptions about COVID-19 and influencing behavior. In this study, we examined the efficacy of a multimodal intervention using authentic social media messages that directly addressed common COVID-19 misconceptions. Going further, we identified individual differences that influenced the effectiveness of the intervention, as well as whether those factors predicted individuals' willingness to receive a COVID-19 vaccine. The results showed that the intervention was successful in increasing knowledge when compared to a baseline control. Those who were older and reported less vaccine hesitancy showed greater learning from the intervention. Factors that significantly predicted intention to vaccinate included receiving the intervention, vaccine confidence, vaccine hesitancy, prior flu vaccination history, age, and fear of COVID-19. These findings indicate that multimodal messages can be effectively leveraged in social media to both fight misinformation and increase intention to be vaccinated - however, these interventions may not be as effective for all individuals.

A Supplementary Approach for Effective Anti-Doping Education: A Pilot Study Applying Refutation Texts to Modify Misperception of the Whereabouts System.

BACKGROUND: Over the past twenty years, a multifaceted anti-doping system was established to detect, deter, and prevent doping among athletes. However, perception of the whereabouts system has been a controversial issue. This pilot study aimed to evaluate the effects of refutation text intervention on the perception of the whereabouts system. METHODS: In two studies, we tested whether (1) detailed refutation texts are perceived as more effective than simply refuting with a true or false claim among 132 athletes (47.73% female, mean age = 20.99 ± 2.11), and if (2) refutation text intervention can alter the perception of the whereabouts system among 177 athletes (53.11% female, mean age = 21.17 ± 2.27). Descriptive statistics were calculated, followed by a one-sample T-test, independent T-test, chi-square test, and a repeated-measures analysis of variance. RESULTS: The results demonstrate that five true/false statements were developed as refutation texts, and the mean accuracy of the true/false test is less than the probability of guess (p < 0.05, d = -0.18). In addition, detailed refutation texts evoked significantly greater perceived effectiveness than the simple refutation texts (p < 0.01, d = 0.66). Furthermore, the refutation text intervention enhanced the positive perception of the whereabouts system (p < 0.01, η2 = 0.15). CONCLUSIONS: Our findings support the efficacy of refutation texts to improve the misperception of anti-doping regimes among athletes and have implications for future education prevention initiatives.

Refutation of traumatic insemination in the Drosophila bipectinata species complex.

Traumatic insemination (TI) is a rare reproductive behaviour characterized by the transfer of sperm to the female via puncture wounds inflicted across her body wall. Here, we challenge the claim made by Kamimura (Kamimura 2007 Biol. Lett.3, 401-404. (doi:10.1098/rsbl.2007.0192)) that males of species of the Drosophila bipectinata complex use a pair of claw-like processes (claws) to traumatically inseminate females: the claws are purported to puncture the female body wall and genital tract, and to inject sperm through the wounds into the lumen of her genital tract, bypassing the vaginal opening. This supposed case of TI is widely cited and featured in prominent subject reviews. We examined high-resolution scanning electron micrographs of the claws and failed to discover any obvious 'groove' for sperm transport. We demonstrated that sperm occurred in the female reproductive tract as a single-integrated unit, inconsistent with the claim that sperm are injected via paired processes. Laser ablation of the sharp terminal ends of the claws failed to inhibit insemination. We showed that the aedeagus in the complex delivers sperm through the vaginal opening, as in other Drosophila. The results refute the claim of TI in the Drosophila bipectinata species complex.

Refutation Text Facilitates Learning: a Meta-Analysis of Between-Subjects Experiments.

Scientific misconceptions are ubiquitous, and in our era of near-instant information exchange, this can be problematic for both public health and the public understanding of scientific topics. Refutation text is one instructional tool for addressing misconceptions and is simple to implement at little cost. We conducted a random-effects meta-analysis to examine the effectiveness of the refutation text structure on learning. Analysis of 44 independent comparisons (n = 3,869) showed that refutation text is associated with a positive, moderate effect (g = 0.41, p < .001) compared to other learning conditions. This effect was consistent and robust across a wide variety of contexts. Our results support the implementation of refutation text to help facilitate scientific understanding in many fields. Supplementary Information: The online version contains supplementary material available at 10.1007/s10648-021-09656-z.

A comparison of prebunking and debunking interventions for implied versus explicit misinformation.

Psychological research has offered valuable insights into how to combat misinformation. The studies conducted to date, however, have three limitations. First, pre-emptive ("prebunking") and retroactive ("debunking") interventions have mostly been examined in parallel, and thus it is unclear which of these two predominant approaches is more effective. Second, there has been a focus on misinformation that is explicitly false, but implied misinformation that uses literally true information to mislead is common in the real world. Finally, studies have relied mainly on questionnaire measures of reasoning, neglecting behavioural impacts of misinformation and interventions. To offer incremental progress towards addressing these three issues, we conducted an experiment (N = 735) involving misinformation on fair trade. We contrasted the effectiveness of prebunking versus debunking and the impacts of implied versus explicit misinformation, and incorporated novel measures assessing consumer behaviours (i.e., willingness-to-pay; information seeking; online misinformation promotion) in addition to standard questionnaire measures. In general, both prebunking and debunking reduced misinformation reliance. We also found that individuals tended to rely more on explicit than implied misinformation both with and without interventions.

Interventions to Dispel Neuromyths in Educational Settings-A Review.

Neuromyths are misconceptions about the brain and learning, for instance Tailoring instruction to students' preferred "learning styles" (e.g., visual, auditory, kinesthetic) promotes learning. Recent reviews indicate that the high prevalence of beliefs in neuromyths among educators did not decline over the past decade. Potential adverse effects of neuromyth beliefs on teaching practices prompted researchers to develop interventions to dispel these misconceptions in educational settings. This paper provides a critical review of current intervention approaches. The following questions are examined: Does neuroscience training protect against neuromyths? Are refutation-based interventions effective at dispelling neuromyths, and are corrective effects enduring in time? Why refutation-based interventions are not enough? Do reduced beliefs in neuromyths translate in the adoption of more evidence-based teaching practices? Are teacher professional development workshops and seminars on the neuroscience of learning effective at instilling neuroscience in the classroom? Challenges, issues, controversies, and research gaps in the field are highlighted, notably the so-called "backfire effect," the social desirability bias, and the powerful intuitive thinking mode. Future directions are outlined.

A rumor reversal model of online health information during the Covid-19 epidemic.

The development of the Internet and social media has expanded the speed and scope of information dissemination, but not all widely disseminated information is true. Especially during the public health emergencies, the endogenous health information demand generated by the lack of scientific knowledge of health information among online users stimulates the dissemination of health information by mass media while providing opportunities for rumor mongers to publish and spread online rumors. Invalid scientific knowledge and rumors will have a serious negative impact and disrupt social order during epidemic outbreaks such as COVID-19. Therefore, it is extremely important to construct an effective online rumor reversal model. The purpose of this study is to build an online rumor reversal model to control the spread of online rumors and reduce their negative impact. From the perspective of internal and external factors, based on the SIR model, this study constructed a G-SCNDR online rumor reversal model by adopting scientific knowledge level theory and an external online rumor control strategy. In this study, the G-SCNDR model is simulated, and a sensitivity analysis of the important parameters of the model is performed. The reversal efficiency of the G-SCNDR model can be improved by properly adopting the isolation-conversion strategy as the external control approach to online rumors with improving the popularization rate of the level of users' scientific knowledge and accelerating the transformation efficiency of official nodes. This study can help provide a better understanding of the process of online rumor spreading and reversing, as well as offering ceritain guidance and countermeasures for online rumor control during public health emergencies.

The effects of experimentally induced emotions on revising common vaccine misconceptions.

Knowledge revision is the process of updating incorrect prior knowledge in light of new, correct information. Although theoretical and empirical knowledge has advanced regarding the cognitive processes involved in revision, less is known about the role of emotions, which have shown inconsistent relations with key revision processes. This study examined the effects of experimentally induced emotions on online and offline knowledge revision of vaccination misconceptions. Before reading refutation and non-refutation texts, 96 individuals received a positive, negative, or no emotion induction. Findings showed that negative emotions, more than positive emotions, resulted in enhanced knowledge revision as indicated by greater ease of integrating correct information during reading and higher comprehension test scores after reading. Findings are discussed with respect to contemporary frameworks of knowledge revision and emotion in reading comprehension and implications for educational practice.

An Attempt to Correct Erroneous Ideas Among Teacher Education Students: The Effectiveness of Refutation Texts.

There is sound evidence about the high prevalence of misconceptions about education among pre-service teachers. This trend continues after students complete the degree in education and once they are in the exercise of their profession. In fact, several studies show that these misconceptions are widespread among in-service teachers. Erroneous ideas about education may divert material and human resources to poor grounded methods and teaching tools, compromising the quality of education. Strategies to debunk misconceptions among future teachers, who may not have a firm position about many educational issues, might contribute to reversing this trend. The main goal of the present study was to assess the efficacy of refutation texts in the correction of misconceptions among pre-service teachers. As in previous studies with in-service teachers, refutation texts were effective in reducing participants' endorsement of misconceptions. But this effect was short-lived and did not affect participants' intention to use educational methods that are based on the misconceptions addressed in the refutation texts.

Refuting misconceptions in medical physiology.

BACKGROUND: In medical physiology, educators and students face a serious challenge termed misconceptions. Misconceptions are incorrect ideas that do not match current scientific views. Accordingly, they have shown to hamper teaching and learning of physiological concepts. Conceptual Change Theory forms the basis of new teaching and learning practices that may alleviate misconceptions and facilitate critical thinking skills that are essential in becoming knowledgeable, self-regulated health professionals. In this study, we examined if such an intervention named refutation texts, could enhance medical students' cognition and metacognition. METHODS: First-year medical students (N = 161) performed a pre-test and post-test on cardiovascular physiology concepts, including a self-perceived confidence rating. In between, students read either a standard text with an explanation of the correct answer, or a refutation text which additionally refuted related misconceptions. RESULTS: In both groups, average performance scores (refutation: + 22.5%, standard: + 22.8%) and overall confidence ratings (refutation: Δ0.42 out of 5, standard: Δ0.35 out of 5) increased significantly (all p < .001), but a significant effect of the specific refutation element was not found. Initially incorrect answers were corrected less frequently in cases of high confidence (35.8%) than low confidence (61.4%). CONCLUSIONS: Our results showed that refutation texts significantly increased students' knowledge, however, the refutation element did not have a significant additional effect. Furthermore, high confidence in incorrect answers negatively affected the likelihood of correction. These findings provide implications for teaching practices on concept learning, by showing that educators should take into account the key role of metacognition, and the nature of misconceptions.

The effects of positive and negative emotional text content on knowledge revision.

Across three experiments, we sought to determine the effects of positive and negative emotional content in refutation texts on misconceptions about vaccines. The addition of negative emotional content to texts that identify, refute, and explain vaccine misconceptions improved knowledge revision observed during reading (Experiment 1). However, the addition of positive emotional content to refutation texts weakened this effect (Experiment 2). A direct comparison between negative and positive emotional content provided corroborating evidence for these findings (Experiment 3). Across experiments, results show that all refutation texts (with or without positive or negative emotional content) improved learning assessed after reading. These findings show the differential effects of emotional content on processing misconceptions about an important socio-scientific topic and provide consistent support for refutation texts as a potentially useful tool in these corrective efforts.

Machine Learning Methods to Predict Social Media Disaster Rumor Refuters.

This research provides a general methodology for distinguishing disaster-related anti-rumor spreaders from a non-ignorant population base, with strong connections in their social circle. Several important influencing factors are examined and illustrated. User information from the most recent posted microblog content of 3793 Sina Weibo users was collected. Natural language processing (NLP) was used for the sentiment and short text similarity analyses, and four machine learning techniques, i.e., logistic regression (LR), support vector machines (SVM), random forest (RF), and extreme gradient boosting (XGBoost) were compared on different rumor refuting microblogs; after which a valid and robust distinguishing XGBoost model was trained and validated to predict who would retweet disaster-related rumor refuting microblogs. Compared with traditional prediction variables that only access user information, the similarity and sentiment analyses of the most recent user microblog contents were found to significantly improve prediction precision and robustness. The number of user microblogs also proved to be a valuable reference for all samples during the prediction process. This prediction methodology could be possibly more useful for WeChat or Facebook as these have relatively stable closed-loop communication channels, which means that rumors are more likely to be refuted by acquaintances. Therefore, the methodology is going to be further optimized and validated on WeChat-like channels in the future. The novel rumor refuting approach presented in this research harnessed NLP for the user microblog content analysis and then used the analysis results of NLP as additional prediction variables to identify the anti-rumor spreaders. Therefore, compared to previous studies, this study presents a new and effective decision support for rumor countermeasures.

Knowledge revision through the lenses of the three-pronged approach.

In the present study, we employed the three-pronged approach to determine the actual cognitive processes theorized in knowledge revision. First, the Knowledge Revision Components (KReC) framework was identified as the guiding theory. Second, think-aloud analysis highlighted at which points in refutation texts readers detected discrepancies between their incorrect, commonsense beliefs and the correct beliefs, and the exact processes with which they dealt with these discrepancies-successfully or unsuccessfully, as indicated by posttest scores. Third, corroborating reading-time data and posttest data demonstrated that the structure of the refutation texts facilitated the coactivation and integration of the explanation with the commonsense belief, resulting in knowledge revision. Finally, an analysis directly connected the processes identified during think-aloud to sentence reading times. These findings systematically identify the cognitive processes theorized during knowledge revision and, in doing so, provide evidence for the conditions for revision outlined in the KReC framework.

The dynamic upper limit of human lifespan.

We respond to claims by Dong et al. that human lifespan is limited below 125 years. Using the log-linear increase in mortality rates with age to predict the upper limits of human survival we find, in contrast to Dong et al., that the limit to human lifespan is historically flexible and increasing. This discrepancy can be explained by Dong et al.'s use of data with variable sample sizes, age-biased rounding errors, and log(0) instead of log(1) values in linear regressions. Addressing these issues eliminates the proposed 125-year upper limit to human lifespan.

Source credibility and the processing of refutation texts.

The knowledge revision components framework (KReC) outlines the basic comprehension processes and text factors that can be accentuated to increase the potential for knowledge revision during reading. The goal of the present study was to explore source credibility as one such text factor. In Experiment 1, we established the utility of a set of refutation texts in influencing knowledge revision. Participants read ten refutation and ten control texts. The participants had faster reading times and higher posttest scores for the refutation than for the control texts, providing evidence for knowledge revision. In Experiment 2, we examined the influence of source credibility under normal reading conditions. Participants read 20 refutation texts, ten with high-credibility and ten with low-credibility sources. The reading times and posttest scores suggested that knowledge revision unfolded successfully, independent of credibility. Using the same texts, in Experiment 3 we examined the influence of direct instructions that made the credibility of the source of information more salient. When the credibility of the source was made salient, the revision process was disrupted in the low-credibility condition, as evidenced by slower reading times and lower posttest scores than in the high-credibility condition. The results add to our understanding of the factors that constrain knowledge revision during the reading of refutation texts, and are discussed in the context of the extant literature and KReC.