Dissertation Abstract

 

 

Semiotics and Advertising

by

Jiang-Ping Fan

 

Degree:           Ph.D.

Year:             2003

Pages:            00221

Institution:      Illinois State University; 0092

Advisor:          Chair Lee Brasseur

 

Source:           DAI, 64, no. 12A (2003): p. 4458

 

This dissertation discusses semiotic theories from three major aspects: the relation of signs (triadic relations proposed by Charles Sanders Peirce, dyadic relations proposed Ferdinand Saussure), the categories of signs (Peirce) and the dimensions of signs (semantics, syntacis, and pragmatics) proposed by Charles Morris. These theories lay a foundation for us to understand how signs, which include both visual and verbal signs, function in our communication.

          Since advertising is a visual intensive genre, the writer of this dissertation used ads from different sources (most of them from State Farm Insurance Companies) to illustrate that we can use the semiotic approach to analyze the use of signs, thus, to interpret their meanings in analytical and design terms. Using the semiotic tool, the writer analyzed over 40 State Farm ads from semantic, syntactic, and pragmatic perspectives to reveal how visual and verbal signs used in State Farm advertising over seventy years reflect the history and business development of the company and the cultural and ideological changes of society as a whole.

          Based on semiotic analysis of ads, the author argues that students of technical communication could benefit from a semiotic approach to documents because semiotics is a prime tool to lead them to a more sophisticated understanding that results in an effective use and interpretation of visuals. In addition, semiotics helps students explore the meanings of visuals and enriches their knowledge about the use of visuals, while at the same time, bettering their critical thinking skills.

 

SUBJECT(S)

Descriptor:       LITERATURE, MODERN

BUSINESS ADMINISTRATION, MARKETING

Accession No:     AAI3115178

Provider:        OCLC

Database:         Dissertations