• Title of article

    Prediction of Instagram Social Network Addiction Based on the Personality, Alexithymia and Attachment Styles

  • Author/Authors

    Ershad, Zeinab Sadat Department of Sociology - Islamic Azad University Tehran Branch, Iran , Aghajani, Tahmoures Department of Sociology - Islamic Azad University West Tehran Branch, Tehran, Iran

  • Pages
    14
  • From page
    21
  • To page
    34
  • Abstract
    Instagram is the fastest growing social network site globally. Instagram is an online, mobile phone photo-sharing, video-sharing, and social network service that enables its users to take pictures and videos, and then share them on other platforms. The purpose of this study is to distinguish the student’s Instagram social network addiction by personality, alexithymia and attachment styles in Tehran city. In this correlational study, a group of 100 high school students (50 Instagram social network addicted and 50 non -addicted) as multi stage sampling are selected. The data collected by the questionnaires of Costa and McCrae (1982) personality scale, Bagboy, Parker and Taylor's twenty-item Toronto alexithymia scale (1994), Collins and Read attachment styles scale (1990) and researcher made Instagram. The obtained data were analyzed by using the technique of discriminated analysis. The results of the discriminant analysis showed that variables of neuroticism, alexithymia, ambivalent and avoidant attachment style can help in predicting how students are involved in Instagram addiction. The study selected 81 percent of the students for their actual classification. The results of this study emphasized on relationship between neuroticism, alexithymia, ambivalent and avoidant attachment style with Instagram addiction. Thus, the prevention and treatment of dependence to Instagram mentioned variables are very important.
  • Keywords
    Discriminant analysis , Instagram , Personality , Alexithymia , Attachment , Students
  • Journal title
    Sociological of Studies of youth
  • Serial Year
    2017
  • Record number

    2523977