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Social cognitive perspectives on personality emphasize the importance of conscious awareness, beliefs, expectations, and goals in shaping behavior. These perspectives incorporate behaviorist principles, such as learning through reinforcement and conditioning, but extend beyond them by highlighting human reasoning and planning. Unlike traditional behaviorist views, social cognitive theory focuses on how individuals reflect on their past experiences and plan for future outcomes by considering...
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Fostering Cyber-Physical Social Systems through an Ontological Approach to Personality Classification Based on Social

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Summary

This study introduces a Romanian language tool for user segmentation based on DISC personality types, analyzing social media posts. The novel approach achieves over 90% accuracy in identifying personality profiles.

Keywords:
DISC personality modelRomanian languagecyber-physical social systemontologypersonality classificationsocial media postsstatement analysis

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Area of Science:

  • Social Computing
  • Cyber-Physical Systems
  • Semantic Technologies

Background:

  • Social networks have accelerated the convergence of cyber-physical systems (CPS) and social computing, leading to smart communities.
  • Social media platforms are crucial for human behavior modeling.
  • Cyber-physical social systems integrate technology and human interaction.

Purpose of the Study:

  • To develop a user segmentation tool for the Romanian language based on the four DISC personality types.
  • To analyze social media statements for personality profiling.
  • To contribute semantic technologies and tools for understanding cyber-physical social systems.

Main Methods:

  • Ontological modeling of personality-specific vocabulary.
  • Mapping vocabulary to social media posts.
  • Utilizing a dataset of nearly 2000 posts from Facebook and Twitter.

Main Results:

  • Developed a novel approach for user segmentation based on DISC personality types.
  • Achieved over 90% accuracy in identifying user personality profiles.
  • Demonstrated the effectiveness of semantic technologies in social media analysis.

Conclusions:

  • The proposed tool offers a scientifically and technologically valuable method for user segmentation.
  • The research has significant business, social, and economic implications for smart communities.
  • This approach enhances the investigation of cyber-physical social systems through personality-driven insights.