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Related Concept Videos

Attribution01:26

Attribution

9
In social interactions, individuals frequently seek to understand the motivations and causes behind others' behaviors. This fundamental aspect of social perception, known as attribution, plays a crucial role in shaping interpersonal relationships and guiding future actions. Attribution refers to the cognitive process through which people infer the reasons behind others' behaviors, allowing them to assess character traits, intentions, and situational influences.Attribution Theory and Its...
9
Attribution Theory00:56

Attribution Theory

13.4K
Behavior is a product of both the situation (e.g., cultural influences, social roles, and the presence of bystanders) and of the person (e.g., personality characteristics). Subfields of psychology tend to focus on one influence or behavior over others. Situationism is the view that our behavior and actions are determined by our immediate environment and surroundings. In contrast, dispositionism holds that our behavior is determined by internal factors (Heider, 1958).
13.4K
Theory of Attribution I: Correspondent Inference Theory01:15

Theory of Attribution I: Correspondent Inference Theory

32
Correspondent inference theory, proposed by Jones and Davis in 1965, seeks to explain how individuals infer stable personality traits from observed behaviors. It suggests that people attribute actions to underlying dispositions rather than external circumstances, particularly when the behavior appears intentional and socially significant.Voluntary Behavior and Dispositional AttributionAccording to this theory, individuals are more likely to attribute behavior to personal traits when it appears...
32
Theory of Attribution II: Kelley's Covariation Theory01:29

Theory of Attribution II: Kelley's Covariation Theory

52
Attribution theory plays a crucial role in social psychology, helping to explain how individuals interpret the causes of behavior. One prominent model within this field is Harold Kelley's covariation theory, which provides a systematic approach to determining whether internal traits or external circumstances drive a person's actions. The model posits that individuals rely on three key types of information—consensus, consistency, and distinctiveness—to make these judgments.Consensus:...
52
Fundamental Attribution Error01:14

Fundamental Attribution Error

13.3K
According to some social psychologists, people tend to overemphasize internal factors as explanations—or attributions—for the behavior of other people. They tend to assume that the behavior of another person is a trait of that person, and to underestimate the power of the situation on the behavior of others. They tend to fail to recognize when the behavior of another is due to situational variables, and thus to the person’s state. This erroneous assumption is...
13.3K
Correspondence Bias01:17

Correspondence Bias

16
Correspondence bias, also referred to as the fundamental attribution error, describes the tendency to attribute another person’s behavior to internal characteristics rather than situational influences. This cognitive bias leads individuals to overlook external factors that may be influencing actions, thereby fostering potentially inaccurate assessments of others’ intentions and dispositions.Empirical Evidence for Correspondence BiasResearch has consistently demonstrated the...
16

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Related Experiment Video

Updated: Oct 7, 2025

Applying Hyperspectral Reflectance Imaging to Investigate the Palettes and the Techniques of Painters
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Attribution Markers and Data Mining in Art Authentication.

Barbara I Łydżba-Kopczyńska1,2, Janusz Szwabiński3

  • 1Faculty of Chemistry, University of Wrocław, F. Joliot-Curie 14, 50-383 Wroclaw, Poland.

Molecules (Basel, Switzerland)
|January 11, 2022
PubMed
Summary
This summary is machine-generated.

Machine learning algorithms, specifically decision trees, show promise in aiding art authentication. This approach can support experts by classifying paintings and potentially reducing investigation costs.

Keywords:
analytical proceduresauthenticationsdata miningforensic analysispaintings

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Area of Science:

  • Art Authentication
  • Machine Learning
  • Decision Support Systems

Background:

  • The global art market faces significant challenges from art forgery, necessitating reliable authentication methods.
  • Current artwork authentication processes are complex, time-pressured, and carry litigation risks.
  • Clinical decision support systems provide a model for potential machine learning applications in art authenticity.

Purpose of the Study:

  • To investigate the utility of machine learning algorithms in supporting the art authenticity examination process.
  • To determine if decision tree models can assist art experts in identifying forged artworks.
  • To explore the potential of machine learning to streamline and reduce the costs of art authentication.

Main Methods:

  • A decision tree model was trained using a dataset of 55 artworks, including 12 known forgeries.
  • Attribution markers for each artwork were determined and used as input for the model.
  • The study drew inspiration from existing clinical decision support systems.

Main Results:

  • Preliminary results indicate that decision trees are a promising technique for supporting art experts.
  • The decision tree model demonstrated the ability to summarize existing knowledge and classify new paintings based on known markers.
  • The method has the potential to identify key attribution markers, thereby reducing investigation costs.

Conclusions:

  • Machine learning, particularly decision trees, offers a viable approach to enhance art authentication.
  • Further development requires larger datasets of artworks with confirmed provenance to build more robust classification models.
  • This technique can aid experts, improve classification accuracy, and potentially lower the financial burden of art investigations.