This paper aims to calculate the factors and build prediction models for the persuasive message changing student’s attitude by applying classification techniques. We used a questionnaire to collect data such as gender, age and their satisfaction with persuasive messages, obtained from students at other country Universities. The classification rule generation process is based on the decision tree as a classification method where the generated rules are studied and evaluated. We compared the results obtained from three algorithms.
data mining, decision tree, persuasive message, significance technology. involvement; health communication
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