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Routes of Persuasion02:20

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Persuasion is the process of changing our attitude toward something based on some kind of communication. Much of the persuasion we experience comes from outside forces. How do people convince others to change their attitudes, beliefs, and behaviors? What communications do you receive that attempt to persuade you to change your attitudes, beliefs, and behaviors?
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Theory of Attribution I: Correspondent Inference Theory01:15

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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...
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Theory of Attribution II: Kelley's Covariation Theory01:29

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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:...
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The Stereotype Content Model (SCM) was first proposed by Susan Fiske and her colleagues (Fiske, Cuddy, Glick & Xu, 2002; see also Fiske, 2012 and Fiske, 2017). The SCM specifies that when someone encounters a new group, they will stereotype them based on two metrics: warmth—or that group’s perceived intent, and how likely they are to provide help or inflict harm—and competence—or their ability to carry out that objective. Depending on the warmth-competence...
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In signal processing, signals are classified based on various characteristics: continuous-time versus discrete-time, periodic versus aperiodic, analog versus digital, and causal versus noncausal. Each category highlights distinct properties crucial for understanding and manipulating signals.
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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).
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Related Experiment Video

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Constructing and Visualizing Models using Mime-based Machine-learning Framework
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Can Algorithms Efficiently Identify Interpretable and Persuasive Message Features? An Agnostic Causal Machine

Sijia Yang1, Luhang Sun1, Ran Tao2

  • 1School of Journalism & Mass Communication, University of Wisconsin-Madison.

Health Communication
|April 21, 2026
PubMed
Summary
This summary is machine-generated.

Discovering effective health messages: Focusing on negative health consequences boosts argument strength and persuasiveness. However, politicizing COVID-19 vaccine messages decreases their effectiveness.

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Area of Science:

  • Communication Science
  • Computational Social Science
  • Health Communication

Background:

  • Developing persuasive health messages requires understanding message-level features.
  • Existing methods for identifying effective message components are often inefficient and lack systematic approaches.

Purpose of the Study:

  • To apply an agnostic causal machine learning approach to systematically uncover message features that enhance argument strength and persuasiveness.
  • To identify specific message content that influences the effectiveness of public health communications.

Main Methods:

  • Utilized a supervised Indian Buffet Process (sIBP) algorithm integrated with AI-facilitated researcher refinement.
  • Employed train/test set splitting and crowdsourcing in two large-scale message experiments.
  • Conducted message-level analyses on tobacco control messages and COVID-19 vaccine promotional messages.

Main Results:

  • Messages emphasizing negative health consequences were found to increase both argument strength and message persuasiveness.
  • Politicizing cues were identified as a factor that reduced the persuasiveness of social media messages promoting COVID-19 vaccines.

Conclusions:

  • An agnostic causal machine learning approach offers an efficient and systematic method for message effects research.
  • Understanding the impact of message content, such as health consequences and politicization, is crucial for designing effective public health campaigns.