Communication Mediation Model vs. Differential Gains

1. Comparing the
Differential Gains and
Communication
Mediation Models
as Predictors of
Political Participation
and Knowledge
Hong Vu, Joseph Yoo, Maegan Stephens, Brian
Barech, Rachel Reis Mourao & Tom Johnson
The University of Texas at Austin
Communication’s Next
Top Model:

2. Introduction
• Well-agreed:
Interpersonal communication works in tandem with
mass communication to influence political
participation and knowledge.
• But which model better explains the relationship
between media, discussion, and political effects?
Differential Gains?
Communication Mediation Model?

3. Literature
• Differential Gains Model (Scheufele and colleagues)
The political effects of news media messages are
contingent upon the media’s interaction with
interpersonal communication.
• Communication Mediation Model (Shah and colleagues)
Mass Communication has an influence on political
aspects but such relationship is indirect:
interpersonal communication mediates the effects

4. Additional Theoretical Inquiry
• Would wider range of media reliance variables
influence the predictive power of the two models?

5. Hypothesesand ResearchQuestions
Interaction effects on political outcomes:
H1- Exposure to news media;
H2- Interaction between news media and face-
to-face communication, and;
H3 - Interaction between news media and online
communication:
 Greater political outcomes (e.g., online, offline
political participation, and knowledge).
Which effects are larger? Direct or interaction?
RQ1 media vs. interaction bt. media & face-to-face;
RQ2 media vs. interaction bt. media & online comm

6. Hypothesesand ResearchQuestions
• Mediation effects on political outcomes:
• H4 – Face-to-face communication:
• H5 – Online communication:
•  Mediate the relationship between news media and
political outcomes.
• Which effects are larger? Mediation or direct?
• RQ3: Media reliance vs. mediation bt. Media & face-
to-face communication.
• RQ4: Media reliance vs. mediation bt. Media & online
communication

7. Method
Amazon Mechanical Turk survey
N = 1267 U.S. respondents
Analysis
Hierarchical regression analysis (Differential Gains Model)
Path analysis (Communication Mediation Model)

8. Independent variables
Online/Offline
FOX/CNN/MSNBC
Newspapers
News Magazines
News & Talk
Radio
Age
Gender
Race
Education
Income
Party Ties
Ideology
Interest
Online Discussion
Interpersonal Discussion
Interaction Variables

9. Dependent variables

10. Results
• Offline political participation is predicted by:
• Media reliance:
• Radio news,
• Fox news
• Political discussion:
• Both online and offline discussion
• Interaction:
• Face-to-face discussion – Fox News;
• Online discussion and print news; radio news; and
Fox news.

11. Results (cont.)
• Online Political participation is predicted by:
• Interaction: print news - online discussion
• Political knowledge is predicted by no variable
• Comparing effects on political participation (RQ1
&RQ2):
• Direct effects of media > interaction - face-to-
face discussion on political participation;
• Effects of media reliance > media interaction –
online discussion

12. Research Questions and Hypotheses

13. Discussion
• Comparison of two models:
• No perfect prediction on either of the two
• Differential Gains: Little support
• Communication Mediation: Considerable support.
• Political discussion should be used as mediation rather
than interaction in predicting political participation
and knowledge.
• Fox News is different from other media variables in
predicting political knowledge and participation.
• Online discussion is important in motivating people to
engage in political activities.