Instagram use, personality traits and how they predict self-esteem
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- Title
- Instagram use, personality traits and how they predict self-esteem
- Creator
- Rebecca Williams
- Supervisor
- Marina Rachitsky and Felix De Beaumont.
- Date
- 2016
- Abstract
- The self-discrepancy theory (SDT) considers that a discrepancy between the ideal and actual self will lead to lower self-esteem (SE). Social networking sites (SNS) have considered how a self-discrepancy in personality and the frequency of use could affect SE. Former studies have mainly considered the SNS Facebook. However, Instagram has become increasingly popular in the past four years, but limited studies have addressed how users are affected on this social media outlet. Potential predictors of Self Esteem (SE) were proposed and investigated in Instagram users aged 18 years and over, with a hypothesis that self-discrepancy scores would be able to predict SE and relationships with frequency of use would also be found. 163 participants completed an online survey measuring self-esteem (RSE), actual personality (NEO FFI) and Instagram use (IUQ). The data were analysed by t-tests, correlations and a hierarchical multiple regression. Multiple regression analysis found that a model including; the self-discrepancy score for neuroticism; actual neuroticism, conscientiousness and extraversion personality scores and the frequency question 'How many images do you upload at one time?' significantly predicted SE. Further comparisons were found between Facebook studies and the current study. The study highlights the importance of continuing research across SNS and how these could impact our personality and SE. Better methods of assessing the different features of SNS are needed. Different measures surrounding questions on SE should also be considered.
- Subject
- Psychology
- Extent
- 74 pages : illustrations
- Format
- Publisher
- Regent's University London
- degree
- MSc Psychology
- Language
- English
- Date Issued
- 2016
- Type
- Thesis & Dissertation
- Rights Holder
- Regent's University London & Rebecca Williams
- Item sets
- Theses or Dissertation