Abstract

AbstractThis paper presents a comprehensive review of persuasion techniques and their applications in the context of designing persuasive communication systems for marketing purposes. The study provides a condensed taxonomy of techniques and offers examples to guide the development of effective persuasive messages. Furthermore, the paper explores how attitudes, personality traits, and emotions can be leveraged as input data in predictive models, including machine learning approaches. The study’s findings offer valuable insights for the design and implementation of persuasive communication systems across diverse contexts, including marketing and advertising, public health campaigns, and political messaging. This paper has the potential to serve as a valuable resource for both researchers and practitioners seeking to enhance their understanding of the science of persuasion, as it synthesizes existing literature and provides practical examples. In this way, the paper contributes to the field of persuasion research and practice, serving as a valuable tool for those seeking to expedite and deepen their knowledge of persuasive communication.

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