scholarly journals The Power of the Truth Bias: False Information Affects Memory and Judgment Even in the Absence of Distraction

2018 ◽  
Vol 36 (2) ◽  
pp. 167-198 ◽  
Author(s):  
Myrto Pantazi ◽  
Mikhail Kissine ◽  
Olivier Klein
Keyword(s):  
False Information ◽  
Truth Bias

International broadcasting: stages of development, specificity and functional structure

2020 ◽  
Vol 4 (4(13)) ◽  
pp. 51-60
Author(s):  
Ksenia Olegovna NEVMERZHITSKAYA ◽  
Keyword(s):  
Foreign Policy ◽  
Global Media ◽  
False Information ◽  
Broadcast Media ◽  
World Community ◽  
Media Agenda ◽  
International Broadcasting ◽  
The World ◽  
The Media ◽  
Media Reports

The media influence politics by providing intelligence and arena for political statements. Therefore, the danger of spreading false information and deliberate disinformation can have serious consequences. It is impossible to accuse specific media outlets of unfair coverage, but one cannot fail to note the existing resonance in media reports from different countries. Interpretations of the same events are radically different, while a journalist must rely on facts. The world is faced with the problem of global misunderstanding and information discord. Modern international broadcasting plays an important role in shaping the picture of the event for the world community. It is impossible to deny that the information agenda of many foreign broadcast media depends to some extent on a number of reasons: nationality, foreign policy of his state, profitability. Otherwise, the global media would not contradict each other. We want to track how modern foreign broadcasting builds its agenda and what principles it is guided by. Keywords: Broadcasting, media, Media agenda

Review and classification of false information systems (FIS)

2020 ◽  
pp. 36-39
Author(s):  
M.A. Kobilev ◽  
E.S. Abramov
Keyword(s):  
Information Systems ◽  
Comparative Analysis ◽  
False Information

The article considers false information systems and conducts their comparative analysis, considering the tasks that they perform, which technologies rely on, and what role is played in protecting information when they are used. The goal is to identify relevant false information systems, to formulate criteria in accordance with which classification is carried out. The problems of false information systems are identified, further work in this topic is determined.

scholarly journals Intelligent Detection of False Information in Arabic Tweets Utilizing Hybrid Harris Hawks Based Feature Selection and Machine Learning Models

Symmetry ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 556
Author(s):  
Thaer Thaher ◽  
Mahmoud Saheb ◽  
Hamza Turabieh ◽  
Hamouda Chantar
Keyword(s):  
Machine Learning ◽  
Social Media ◽  
Feature Selection ◽  
Language Processing ◽  
User Profile ◽  
Vital Role ◽  
Classification Model ◽  
Fake News ◽  
False Information ◽  
Social Media Platforms

Fake or false information on social media platforms is a significant challenge that leads to deliberately misleading users due to the inclusion of rumors, propaganda, or deceptive information about a person, organization, or service. Twitter is one of the most widely used social media platforms, especially in the Arab region, where the number of users is steadily increasing, accompanied by an increase in the rate of fake news. This drew the attention of researchers to provide a safe online environment free of misleading information. This paper aims to propose a smart classification model for the early detection of fake news in Arabic tweets utilizing Natural Language Processing (NLP) techniques, Machine Learning (ML) models, and Harris Hawks Optimizer (HHO) as a wrapper-based feature selection approach. Arabic Twitter corpus composed of 1862 previously annotated tweets was utilized by this research to assess the efficiency of the proposed model. The Bag of Words (BoW) model is utilized using different term-weighting schemes for feature extraction. Eight well-known learning algorithms are investigated with varying combinations of features, including user-profile, content-based, and words-features. Reported results showed that the Logistic Regression (LR) with Term Frequency-Inverse Document Frequency (TF-IDF) model scores the best rank. Moreover, feature selection based on the binary HHO algorithm plays a vital role in reducing dimensionality, thereby enhancing the learning model’s performance for fake news detection. Interestingly, the proposed BHHO-LR model can yield a better enhancement of 5% compared with previous works on the same dataset.

scholarly journals Prevalence of Missing Values and Protest Zeros in Contingent Valuation in Dental Medicine

2021 ◽  
Vol 18 (14) ◽  
pp. 7219
Author(s):  
Pedram Sendi ◽  
Arta Ramadani ◽  
Michael M. Bornstein
Keyword(s):  
Contingent Valuation ◽  
Missing Values ◽  
Web Of Science ◽  
Cochrane Library ◽  
Future Research ◽  
False Information ◽  
Complete Case ◽  
Zero Values ◽  
Elicitation Procedure

Background: The number of contingent valuation (CV) studies in dental medicine using willingness-to-pay (WTP) methodology has substantially increased in recent years. Missing values due to absent information (i.e., missingness) or false information (i.e., protest zeros) are a common problem in WTP studies. The objective of this study is to evaluate the prevalence of missing values in CV studies in dental medicine, to assess how these have been dealt with, and to suggest recommendations for future research. Methods: We systematically searched electronic databases (MEDLINE, Web of Science, Cochrane Library, PROSPERO) on 8 June 2021, and hand-searched references of selected reviews. CV studies in clinical dentistry using WTP for valuing a good or service were included. Results: We included 49 WTP studies in our review. Out of these, 19 (38.8%) reported missing values due to absent information, and 28 (57.1%) reported zero values (i.e., WTP valued at zero). Zero values were further classified into true zeros (i.e., representing the underlying preference of the respondent) or protest zeros (i.e., false information as a protest behavior) in only 9 studies. Most studies used a complete case analysis to address missingness while only one study used multiple imputation. Conclusions: There is uncertainty in the dental literature on how to address missing values and zero values in CV studies. Zero values need to be classified as true zeros versus protest zeros with follow-up questions after the WTP elicitation procedure, and then need to be handled differently. Advanced statistical methods are available to address both missing values due to missingness and due to protest zeros but these are currently underused in dental medicine. Failing to appropriately address missing values in CV studies may lead to biased WTP estimates of dental interventions.

scholarly journals Black and White Lies: Race-Based Biases in Deception Judgments

2017 ◽  
Vol 28 (8) ◽  
pp. 1125-1136 ◽  
Author(s):  
E. Paige Lloyd ◽  
Kurt Hugenberg ◽  
Allen R. McConnell ◽  
Jonathan W. Kunstman ◽  
Jason C. Deska
Keyword(s):  
Law Enforcement ◽  
Eye Tracking ◽  
Interpersonal Relationships ◽  
Late Stage ◽  
Racial Bias ◽  
Lie Detection ◽  
Intergroup Communication ◽  
Black And White ◽  
Truth Bias ◽  
Practical Implications

In six studies ( N = 605), participants made deception judgments about videos of Black and White targets who told truths and lies about interpersonal relationships. In Studies 1a, 1b, 1c, and 2, White participants judged that Black targets were telling the truth more often than they judged that White targets were telling the truth. This truth bias was predicted by Whites’ motivation to respond without prejudice. For Black participants, however, motives to respond without prejudice did not moderate responses (Study 2). In Study 3, we found similar effects with a manipulation of the targets’ apparent race. Finally, in Study 4, we used eye-tracking techniques to demonstrate that Whites’ truth bias for Black targets is likely the result of late-stage correction processes: Despite ultimately judging that Black targets were telling the truth more often than White targets, Whites were faster to fixate on the on-screen “lie” response box when targets were Black than when targets were White. These systematic race-based biases have important theoretical implications (e.g., for lie detection and improving intergroup communication and relations) and practical implications (e.g., for reducing racial bias in law enforcement).

Gating Out Misinformation: Can Young Children Follow Instructions to Ignore False Information?

2015 ◽  
Vol 33 (4) ◽  
pp. 390-406 ◽  
Author(s):  
Jennifer M. Schaaf ◽  
Daniel Bederian-Gardner ◽  
Gail S. Goodman
Keyword(s):  
Young Children ◽  
False Information

Deception, Detection, Demeanor, and Truth Bias in Face-to-Face and Computer-Mediated Communication

2013 ◽  
Vol 42 (8) ◽  
pp. 1116-1142 ◽  
Author(s):  
Lyn M. Van Swol ◽  
Michael T. Braun ◽  
Miranda R. Kolb
Keyword(s):  
Deception Detection ◽  
Computer Mediated Communication ◽  
Mediated Communication ◽  
Face To Face ◽  
Truth Bias ◽  
Computer Mediated

Intelligent Legal Decision Support System to Classify False Information on Social Media

2020 ◽  
pp. 258-272
Author(s):  
Arsenii Tretiakov ◽  
Elizaveta Kobets ◽  
Natalia Gorlushkina ◽  
Viktor Kumpan ◽  
Alexandra Basakina
Keyword(s):  
Social Media ◽  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Legal Decision ◽  
False Information

scholarly journals EpiCore: Crowdsourcing Health Professionals to Verify Disease Outbreaks

2017 ◽  
Vol 9 (1) ◽  
Author(s):  
Jennifer Olsen
Keyword(s):  
Health Professionals ◽  
Situational Awareness ◽  
Signal To Noise Ratio ◽  
Disease Outbreaks ◽  
Local Information ◽  
Outbreak Detection ◽  
False Information ◽  
The World ◽  
Geographic Regions ◽  
Human Animal

IntroductionEpiCore draws on the knowledge of a global community of human,animal, and environmental health professionals to verify informationon disease outbreaks in their geographic regions. By using innovativesurveillance techniques and crowdsourcing these experts, EpiCoreenables faster global outbreak detection, verification, and reporting.MethodsThrough a secure online platform, members are able to easily andquickly provide local information to expedite outbreak verification.EpiCore volunteer applications are vetted to ensure that they possessthe public health and epidemiologic expertise necessary to contributeto the platform.ResultsEpiCore currently has over 1600 members that span 135 countries.During the first 8 months of EpiCore’s launch, 172 requests forinformation to volunteers have been posted with an average responserate of over 80%.ConclusionsWith its geographical distribution of members and high responserate, EpiCore is poised to enable the world to verify potential outbreaksignals faster. By improving situational awareness, de-escalatingrumors or false information, and corroborating using other existingsources, EpiCore is able to reduce the signal to noise ratio in diseasesurveillance. Hence, by detecting and verifying outbreaks faster,health officials can generate early responses that can curb epidemicsand save lives.

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