The psychological interaction of spam email features

Area of Science:

• Cognitive Psychology
• Human-Computer Interaction
• Information Security

Background:

• Spam email classification relies on user perception and decision-making.
• Understanding the cognitive processes behind spam detection is crucial for improving user awareness and training.

Purpose of the Study:

• To investigate the distinct perceptual and decisional factors influencing mental construal of spam emails.
• To apply General Recognition Theory (GRT) to model how users classify spam based on features like prose quality, message structure, and premise plausibility.

Main Methods:

• Participants classified spam emails varying in prose quality, message structure, and premise plausibility.
• General Recognition Theory (GRT), a multidimensional extension of signal detection theory, was used for data modeling.
• Analysis focused on dimensional interactions, perceptual discriminability, and decision criteria.

Main Results:

• Classification accuracy was highest for emails with either two abnormal or two normal feature levels.
• Both perceptual and decisional contributions significantly influenced classification responses.
• Perceptual discriminability and decision criteria were biased by the presence of abnormal features in paired dimensions.

Conclusions:

• The study successfully modeled perceptual and decisional biases in spam email classification using GRT.
• Findings highlight the interplay between different stimulus dimensions in user judgment.
• Identified biases offer potential for individualizing anti-spam training programs.