Advertising and Media

Stuart Ewen's Captains of Consciousness: Advertising and the Social Roots of the Consumer Culture (New York: McGraw-Hill, 1976---$10.00)

Wilson Bryan Key's Media Sexploitation (Englewood Cliffs, N.J.: Prentice-Hall, 1976---$8.95)

Jib Fowles's Mass Advertising as Social Forecast: A Method for Futures Research (Westport, Conn.: Greenwood Press, 1976---$10.95)

James E. Combs and Michael W. Mansfield (eds.) Drama in Life: The Uses of Communication in Society (New York: Hastings House, 1976---$18.50/10.50)

Walter E. Hurst and Don Rico's How to Be a Music Publisher (Seven Arts Press, 6605 Hollywood Blvd., Hollywood, Calf. 90026---$10.00 paper)     

The 2008 Presidential Campaign: Political Cynicism in the Age of Facebook,MySpace, and YouTube

Considerable research over the years has been devoted to ascertaining the impact of media use on political cynicism. The impact of the Internet has been difficult to assess because it is not a single monolithic medium. For example, the 2008 presidential campaign was the first presidential campaign in which popular social networking sites such as Facebook, MySpace, and YouTube were widely available to voters. Therefore, the campaign offered the first opportunity to explore the influence of these social media on political cynicism. In this study, we examined whether the use of such social media influenced political cynicism. We also considered the influence of user background characteristics (e.g., self-efficacy, locus of control, political orientation, demographics, and influence of family and friends), motives for using social media for political information, and users’ elaboration on political content. Several individual differences were stronger predictors of political cynicism than was social media use. In fact, social networking use was a negative predictor of political cynicism. Results supported uses and gratifications’ notions that the influence of social media on political cynicism is more attributable to user background and media-use differences than to sheer use of these popular sites.     

Navigational Structures and Information Selection Goals: A Closer Look at Online Selectivity

Using an experimental design coupled with Web-tracking technology, this study explores 2 factors that influence levels of congruent information gathering online. The first factor compares the navigational structure of 2 distinct Web pages—the more open, user-directed search engine versus the organized, assembled structure of a portal Web page. The second factor tests the role of goals for information seeking—telling subjects they will soon engage in a discussion with another person who either disagrees with their viewpoint, agrees, is undecided, or no discussion treatment. Results indicate both experimental factors independently contribute to selectivity in online information seeking.     

The Role of Values in Predicting Talk Radio Listening: A Model of Value Equivalence

Nontraditional sources of news, such as talk radio and the Internet, complement and sometimes replace traditional mainstream news sources. Using discriminant function analysis, this study reveals the role of values in predicting listening to political talk and religious radio programs. A model using the construct of “value equivalence” explains value differences between user and media that may affect whether or not news from nontraditional sources will be sought and used. Research questions are answered using data from the 2004 Pew Research Center Biennial Consumption Survey. Using selected independent variables (including value-based variables) to predict listening to the Rush Limbaugh program, 59% of all cases in this study were correctly classified. Using the same set of value-based variables to predict listening to religious radio shows yielded nearly 74% correctly classified cases.     

A Note on Cluster Effects in Latent Class Analysis

This article examines the effects of clustering in latent class analysis. A comprehensive simulation study is conducted, which begins by specifying a true multilevel latent class model with varying within- and between-cluster sample sizes, varying latent class proportions, and varying intraclass correlations. These models are then estimated under the assumption of a single-level latent class model. The outcomes of interest are measures of bias in the Bayesian Information Criterion (BIC) and the entropy R ² statistic relative to accounting for the multilevel structure of the data. The results indicate that the size of the intraclass correlation as well as between- and within-cluster sizes are the most prominent factors in determining the amount of bias in these outcome measures, with increasing intraclass correlations combined with small between-cluster sizes resulting in increased bias. Bias is particularly noticeable in the BIC. In addition, there is evidence that class separation interacts with the size of the intraclass correlations and cluster sizes in producing bias in these measures.     

Put Theory Into Practice

Audrey J. Jaeger, Stephany Dunstan, Courtney Thornton, Alyssa B. Rockenbach, Joy G. Gayles, and Karen J. Haley argue that applying our theoretical frameworks in everyday decision making will help us to be more efficient and effective—and they provide a user‐friendly analogy to guide us in this endeavor.