Date of Award

2001

Degree Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Department

Communication

First Advisor

Paul Messaris

Abstract

Many scholars believe that news images affect public opinion about political and social issues. Previous research has shown that emotionally evocative visual news texts improve learning and memory for information as well as affect audience perspectives on relevant issues. However, the majority of these studies do not address in detail what combinations of characteristics create emotionally compelling images. Through content analysis of news photographs and both quantitative and qualitative measurement of viewer’s response to those images, this study begins to define what visual characteristics contribute significantly to emotional impact. The results of the content analysis also contribute to our understanding of what types of photographs appear most frequently in the news. The results show that features generally characterized by communication researchers as improving memory and learning: extreme negativity and deviation from normal visual experience were not well represented among the sample of 400 photographs from the Associated Press Photo Archive. Although the majority of photographs (65%) did have negative themes, only 5% of the images showed any kind of violence. Ten percent displayed the outcome of a non-violent disaster. The large majority of pictures were also photographed using vertical camera axes and straight angles. A sample of images from the iv content analysis was used as stimuli in the viewer-response portion of the study. Measures of the content served as independent variables in two regression analyses. The dependent variables were viewers’ level of either positive or negative affect. Significant predictors of negative affect included the presence of violence, the effects of violence, and the effects of disaster. Negative emotional displays by the subject(s) of the image, and unusual juxtapositions of people and/or objects also predicted negative affect. A separate regression analysis was conducted for positive affect. The presence of violence, unusual juxtapositions of objects, and negative emotional displays had significant, but negative, relationships with positive affect. Positive emotional displays and viewing the more central subjects in the image from the front significantly and directly predicted positive affect. Finally, the degree of closeness among subjects in the image also significantly predicted positive affect. Analysis of open-ended responses generally supports these results.

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