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Related Concept Videos

Understanding Deception01:14

Understanding Deception

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Deception is a pervasive aspect of human communication. Empirical studies have shown that most individuals engage in some form of deceit on a daily basis, with approximately 20% of social exchanges involving deceptive elements. Lying follows a developmental trajectory, peaking during adolescence and declining with age, possibly due to the maturation of cognitive control and social accountability.Cognitive and Social Factors in Deception DetectionDespite its prevalence, accurately detecting...
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Person perception is influenced by both external behaviors and the observer’s internal characteristics, including personality traits. Individuals with dark personality traits, comprising psychopathy, Machiavellianism, and narcissism — collectively known as the dark triad – exhibit manipulative and exploitative tendencies in social contexts. These traits affect how they perceive others and how they are perceived.The Role of Dark Personality Traits in Person PerceptionBlack et...
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Social proof is a form of persuasion based on comparison and conformity. People compare their behavior and actions to what others are doing and will change to conform to do what their peers do.
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False memories represent a cognitive distortion in which individuals recall events that did not happen, or remember them in an altered form. This phenomenon highlights the brain's constructive nature in processing and recalling memories, emphasizing that memory is not a perfect representation of past events but rather a dynamic reconstruction influenced by various factors.
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Impression Management Techniques II: Ingratiation01:29

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Ingratiation refers to deliberate behaviors aimed at increasing one’s attractiveness or likability to a target person, often for strategic interpersonal or social gain. This set of impression management tactics is especially prevalent in hierarchical contexts, where influencing someone with greater power or authority can yield significant benefits. Several distinct ingratiation strategies have been identified, each leveraging psychological cues to foster favor and affiliation.Opinion...
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The confirmation bias is the tendency to focus on information that confirms our existing beliefs and ignore information that is inconsistent with our expectations. For example, if you think that your professor is not very nice, you notice all of the instances of rude behavior exhibited by the professor while ignoring the countless pleasant interactions he is involved in on a daily basis. Have you ever fallen prey to the confirmation bias, either as the source or target of such bias?
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Related Experiment Video

Updated: Oct 1, 2025

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention
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Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention

Published on: December 15, 2023

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Deep Learning-Based Fake Information Detection and Influence Evaluation.

Ning Xiang1

  • 1School of Journalism and Communication, Hunan Mass Media Vocational and Technical College, Changsha 410100, China.

Computational Intelligence and Neuroscience
|March 7, 2022
PubMed
Summary
This summary is machine-generated.

This study introduces a novel multimodal fake information detection method using text and visual data from online social networks. The approach significantly outperforms existing methods in accuracy, precision, recall, and F1 score.

Related Experiment Videos

Last Updated: Oct 1, 2025

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention
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Area of Science:

  • Computer Science
  • Artificial Intelligence
  • Information Science

Background:

  • Online Social Networks (OSN) are primary news sources, but rife with misinformation.
  • Effective fake information detection is crucial in the digital age.

Purpose of the Study:

  • To propose a multimodal fake information detection method.
  • To leverage both textual and visual content for improved detection accuracy.

Main Methods:

  • Utilized Bert for textual feature representation.
  • Employed VGG-19 for visual feature representation.
  • Implemented two Multimodal Compact Bilinear Pooling (MCBP) modules, incorporating attention mechanisms for feature fusion.

Main Results:

  • The proposed method achieved superior performance compared to EANN and SpotFake.
  • Demonstrated improvements across accuracy, precision, recall, and F1 score metrics.
  • Validated effectiveness on Twitter and Weibo datasets.

Conclusions:

  • The multimodal approach effectively detects fake information.
  • Attention-based feature fusion enhances detection capabilities.
  • This method offers a promising solution for combating online misinformation.