The Persuasive Power of Campaign Advertising

by Ridout, Travis N.; Franz, Michael M.

• ISBN13: 9781439903339
• ISBN10: 1439903336
• Format: Paperback
• Copyright: 2011-03-25
• Publisher: Temple Univ Pr

Summary

The Persuasive Power of Campaign Advertisingoffers a comprehensive overview of political advertisements and their changing role in the Internet age. Travis Ridout and Michael Franz examine how these ads function in various kinds of campaigns and how voters are influenced by them.The authors particularly study where ads are placed, asserting that television advertising will still be relevant despite the growth of advertising on the Internet. The authors also explore the recent phenomenon of outrageous ads that "go viral" on the web-which often leads to their replaying as television news stories, generating additional attention. The Persuasive Power of Campaign Advertisingfeatures the first analysis of the impact on voters of media coverage of political advertising and shows that televised political advertising continues to have widespread influence on the choices that voters make at the ballot box.

Author Biography

Travis N. Ridout is Associate Professor of Political Science at Washington State University and a coauthor (with Michael M. Franz, Paul B. Freedman, and Kenneth M. Goldstein) of Campaign Advertising and American Democracy (Temple). Michael M. Franz is Associate Professor of Government and Legal Studies at Bowdoin College, author of Choices and Changes: Interest Groups in the Electoral Process, and a coauthor (with Paul B. Freedman, Kenneth M. Goldstein, and Travis N. Ridout) of Campaign Advertising and American Democracy (Temple).

Table of Contents

Preface	p. vii
The Role of Campaign Advertising	p. 1
The Problem of Persuasion	p. 21
A Brief Primer on Data and Research Design	p. 37
How Race Context Matters	p. 51
How Negativity and Emotional Appeals in Ads Matter	p. 79
How Receivers' Characteristics Matter	p. 103
How Ad Coverage in News Matters	p. 123
The Future Study of Ad Effects	p. 145
Variable Coding	p. 153
Full Model Results from Chapter 4	p. 161
Additional Model Results from Chapter 5	p. 169
References	p. 171
Index	p. 181
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