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Uncertainty Reduction Theory
Charles Berger

INTERPERSONAL COMMUNICATION: RELATIONSHIP DEVELOPMENT

Chapter 9
 Social Penetration Theory
Social Information Processing... 
Chapter 9
 Social Penetration Theory
Social Information Processing... 

Chapter Outline 9th Edition

  1. Introduction.
    1. Charles Berger notes that the beginnings of personal relationships are fraught with uncertainties.
    2. Uncertainty reduction theory focuses on how human communication is used to gain knowledge and create understanding.
    3. Any of three prior conditions—anticipation of future interaction, incentive value, or deviance—can boost our drive to reduce uncertainty.
  2. Uncertainty reduction: To predict and explain.
    1. Berger’s emphasis on explanation (our inferences about why people do what they do) comes from the attribution theory of Fritz Heider.
    2. There are at least two types of uncertainty.
      1. Behavioral questions, which are often reduced by following accepted procedural protocols.
      2. Cognitive questions, which are reduced by acquiring information.
  3. An axiomatic theory: Certainty about uncertainty.
    1. Berger proposes a series of axioms to explain the connection between uncertainty and eight key variables.
    2. Axiom 1, verbal communication: As the amount of verbal communication between strangers increases, the level of uncertainty decreases, and as a result, verbal communication increases.
    3. Axiom 2, nonverbal warmth: As nonverbal affiliative expressiveness increases, uncertainty levels will decrease.  Decreases in uncertainty level will cause increases in nonverbal affiliative expressiveness.
    4. Axiom 3, information seeking: High levels of uncertainty cause increases in information-seeking behavior.  As uncertainty levels decline, information-seeking behavior decreases.
    5. Axiom 4, self-disclosure: High levels of uncertainty in a relationship cause decreases in the intimacy level of communication content.  Low levels of uncertainty produce high levels of intimacy.
    6. Axiom 5, reciprocity: High levels of uncertainty produce high rates of reciprocity.  Low levels of uncertainty produce low levels of reciprocity.
    7. Axiom 6, similarity: Similarities between persons reduce uncertainty, while dissimilarities produce increases in uncertainty.
    8. Axiom 7, liking:  Increases in uncertainty level produce decreases in liking; decreases in uncertainty produce increases in liking.
    9. Axiom 8, shared networks: Shared communication networks reduce uncertainty, while a lack of shared networks increases uncertainty.
  4. Theorems: The logical force of uncertainty axioms.
    1. Through pairing axioms, Berger creates 28 theorems.
    2. These 28 theorems suggest a comprehensive theory of interpersonal development based on the importance of reducing uncertainty in human interaction.
  5. Message plans to cope with uncertain responses.
    1. Berger concluded that most social interaction is goal-driven: we have reasons for saying what we say.
      1. Berger claims plans are hierarchically organized with abstract representations at the top of the hierarchy and progressively more concrete representation toward the bottom.
      2. Switching strategies at the top of the hierarchy causes changes down the hierarchy, altering behavior.
    2. Uncertainty is central to all social interaction.
    3. There is an interaction between uncertainty reduction theory and plan-based message production that suggests various strategies individuals use to cope with uncertainty and hedge against risk when deploying messages.
      1. Seeking information through a passive, active, or interactive strategy.
      2. Choosing plan complexity—the level of detail a plan includes and the number of contingency plans.
      3. Hedging—planning ways for both parties to “save face” when at least one of them miscalculated.
      4. The hierarchy hypothesis: When individuals are thwarted in their attempts to achieve goals, their first tendency is to alter lower-level elements of their message.
  6. Critique: Nagging doubts about uncertainty.
    1. As Berger himself admits, his original statement contained some propositions of dubious validity.
      1. Critics such as Kathy Kellermann consider theorem 17 particularly flawed.
      2. The tight logical structure of the theory doesn't allow us to reject one theorem without questioning the axioms behind it.
      3. In the case of theorem 17, axioms 3 and 7 must also be suspect.
      4. Kellermann and Rodney Reynolds challenge the motivational assumption of axiom 3.
      5. They also have undermined the claim that motivation to search for information is increased by anticipation of future interaction, incentive value, and deviance.
    2. Michael Sunnafrank challenges Berger’s claim that uncertainty reduction is the key to understanding early encounters.
      1. He believes that predicted outcome value more accurately explains communication in early encounters.
      2. Berger insists that you can't predict outcome values until you reduce uncertainty.
    3. Walid Afifi thinks both theories are too narrow. In his theory of motivated information management, he suggests we’re most motivated to reduce anxiety rather than uncertainty.
    4. Despite these problems, Berger's theory has stimulated considerable discussion within the discipline.

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For the full list of resources
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Instructors can get additional
resources. Read more













TEXT COMPARE

Archived chapters (PDF)
from previous editions
are available in
Resources by Type.
See list

New to Theory
Resources?
Find out more in this short
video overview (3:01).


Uncertainty Reduction Theory
Charles Berger

INTERPERSONAL COMMUNICATION: RELATIONSHIP DEVELOPMENT

Chapter 9
 Social Penetration Theory
Social Information Processing... 
Chapter 9
 Social Penetration Theory
Social Information Processing... 

Chapter Outline 9th Edition

  1. Introduction.
    1. Charles Berger notes that the beginnings of personal relationships are fraught with uncertainties.
    2. Uncertainty reduction theory focuses on how human communication is used to gain knowledge and create understanding.
    3. Any of three prior conditions—anticipation of future interaction, incentive value, or deviance—can boost our drive to reduce uncertainty.
  2. Uncertainty reduction: To predict and explain.
    1. Berger’s emphasis on explanation (our inferences about why people do what they do) comes from the attribution theory of Fritz Heider.
    2. There are at least two types of uncertainty.
      1. Behavioral questions, which are often reduced by following accepted procedural protocols.
      2. Cognitive questions, which are reduced by acquiring information.
  3. An axiomatic theory: Certainty about uncertainty.
    1. Berger proposes a series of axioms to explain the connection between uncertainty and eight key variables.
    2. Axiom 1, verbal communication: As the amount of verbal communication between strangers increases, the level of uncertainty decreases, and as a result, verbal communication increases.
    3. Axiom 2, nonverbal warmth: As nonverbal affiliative expressiveness increases, uncertainty levels will decrease.  Decreases in uncertainty level will cause increases in nonverbal affiliative expressiveness.
    4. Axiom 3, information seeking: High levels of uncertainty cause increases in information-seeking behavior.  As uncertainty levels decline, information-seeking behavior decreases.
    5. Axiom 4, self-disclosure: High levels of uncertainty in a relationship cause decreases in the intimacy level of communication content.  Low levels of uncertainty produce high levels of intimacy.
    6. Axiom 5, reciprocity: High levels of uncertainty produce high rates of reciprocity.  Low levels of uncertainty produce low levels of reciprocity.
    7. Axiom 6, similarity: Similarities between persons reduce uncertainty, while dissimilarities produce increases in uncertainty.
    8. Axiom 7, liking:  Increases in uncertainty level produce decreases in liking; decreases in uncertainty produce increases in liking.
    9. Axiom 8, shared networks: Shared communication networks reduce uncertainty, while a lack of shared networks increases uncertainty.
  4. Theorems: The logical force of uncertainty axioms.
    1. Through pairing axioms, Berger creates 28 theorems.
    2. These 28 theorems suggest a comprehensive theory of interpersonal development based on the importance of reducing uncertainty in human interaction.
  5. Message plans to cope with uncertain responses.
    1. Berger concluded that most social interaction is goal-driven: we have reasons for saying what we say.
      1. Berger claims plans are hierarchically organized with abstract representations at the top of the hierarchy and progressively more concrete representation toward the bottom.
      2. Switching strategies at the top of the hierarchy causes changes down the hierarchy, altering behavior.
    2. Uncertainty is central to all social interaction.
    3. There is an interaction between uncertainty reduction theory and plan-based message production that suggests various strategies individuals use to cope with uncertainty and hedge against risk when deploying messages.
      1. Seeking information through a passive, active, or interactive strategy.
      2. Choosing plan complexity—the level of detail a plan includes and the number of contingency plans.
      3. Hedging—planning ways for both parties to “save face” when at least one of them miscalculated.
      4. The hierarchy hypothesis: When individuals are thwarted in their attempts to achieve goals, their first tendency is to alter lower-level elements of their message.
  6. Critique: Nagging doubts about uncertainty.
    1. As Berger himself admits, his original statement contained some propositions of dubious validity.
      1. Critics such as Kathy Kellermann consider theorem 17 particularly flawed.
      2. The tight logical structure of the theory doesn't allow us to reject one theorem without questioning the axioms behind it.
      3. In the case of theorem 17, axioms 3 and 7 must also be suspect.
      4. Kellermann and Rodney Reynolds challenge the motivational assumption of axiom 3.
      5. They also have undermined the claim that motivation to search for information is increased by anticipation of future interaction, incentive value, and deviance.
    2. Michael Sunnafrank challenges Berger’s claim that uncertainty reduction is the key to understanding early encounters.
      1. He believes that predicted outcome value more accurately explains communication in early encounters.
      2. Berger insists that you can't predict outcome values until you reduce uncertainty.
    3. Walid Afifi thinks both theories are too narrow. In his theory of motivated information management, he suggests we’re most motivated to reduce anxiety rather than uncertainty.
    4. Despite these problems, Berger's theory has stimulated considerable discussion within the discipline.

 
 
 
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