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Associations of Personality Traits and Emotional Intelligence In Social Network Consumers via Data Mining Techniques

Author

Listed:
  • Stamoulis, Giorgos
  • Papavasileiou, Niovi
  • Gkintoni, Evgenia
  • Halkiopoulos, Constantinos

    (University of Patras, Greece)

  • Antonopoulou, Hera

Abstract

The present study aims to investigate personality traits and emotional intelligence in young adults’ consumers who use social networks to make shopping. Consumer behavior has long been of interest to researchers. Contemporary research on Consumer Behavior considers a wide range of factors influencing the consumer,and acknowledges a broad range of consumption activities beyond purchasing. Νowadays, since online purchases is a daily practice, it is useful to study the behavior of online consumers who are social network users and make shopping via social media. Two basic components that influence consumer behavior are personality and emotional intelligence. Emotional intelligence is both characteristic of personality and intellectual capacity, which a person inherits from the genetic material of its parents and evolves - develops throughout lifetime. Personality’ refers to the pattern of thoughts, feelings and behavior that makes each individual separate from others. These affect the way of think, feeling and behaving towards itself and others. The data were collected by completion of the self-report questionnaire Trait Emotional Intelligence (TEIQue), as far as emotional intelligence concerned, and the Eysenck Personality Questionnaire (EPQ) as far as personality traits of personality disorders concerned. Specifically, for the collection of data electronic questionnaire TEIQue and EPQ were being created through Google Forms service and posted through the website “http://www.cicos.gr/iccmi2017/aptei”. Then the collected data were selected for analysis, with relevant transformations in order to have a suitable form for the implementation of the respective machine learning algorithms included in the software package R. Furthermore, the parameters of the corresponding set of algorithms were determined depending on the case of application to produce inference rules. Some of the algorithms implemented according to specific research questions that were applied, were the classification algorithms for the production of decision trees, regarding the four more general factors (welfare, self-control, emotionality and sociability) of emotional intelligence and also personality traits of social network consumers. The results obtained, after weighing and criteria basis, present consumers' rates, which in turn analyze the degree of emotional intelligence and personality traits. Personality and emotional intelligence index can play a crucial role in clarifying consumer behavior of social network users.

Suggested Citation

  • Stamoulis, Giorgos & Papavasileiou, Niovi & Gkintoni, Evgenia & Halkiopoulos, Constantinos & Antonopoulou, Hera, 2017. "Associations of Personality Traits and Emotional Intelligence In Social Network Consumers via Data Mining Techniques," OSF Preprints 8qtak, Center for Open Science.
    • Handle: RePEc:osf:osfxxx:8qtak
    DOI: 10.31219/osf.io/8qtak
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    References listed on IDEAS

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    1. Gkintoni, Evgenia & Togias, Panagiotis & Halkiopoulos, Constantinos & Giotopoulos, Konstantinos & Antonopoulou, Hera, 2016. "Burnout: Emerged Issue in Business during Economic Recession in Greece," OSF Preprints gnqsx, Center for Open Science.
    2. Gerasimos Panas & Georgios Heliades & Constantinos Halkiopoulos & Dimitra Tsavalia & Argyro Bougioura, 2017. "Evaluation of Athens as a City Break Destination: Tourist Perspective Explored via Data Mining Techniques," Springer Proceedings in Business and Economics, in: Vicky Katsoni & Amitabh Upadhya & Anastasia Stratigea (ed.), Tourism, Culture and Heritage in a Smart Economy, pages 85-103, Springer.
    3. Petrides, K.V., 2010. "Trait Emotional Intelligence Theory," Industrial and Organizational Psychology, Cambridge University Press, vol. 3(2), pages 136-139, June.
    4. Georgios Heliades & Constantinos Halkiopoulos & Dimitrios Arvanitis, 2017. "Dissemination of Environmental Soundscape and Musical Heritage Through 3D Virtual Telepresence," Springer Proceedings in Business and Economics, in: Vicky Katsoni & Amitabh Upadhya & Anastasia Stratigea (ed.), Tourism, Culture and Heritage in a Smart Economy, pages 19-34, Springer.
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