Lying or longing for likes? Narcissism, peer belonging, loneliness and normative versus deceptive like-seeking on Instagram in emerging adulthood
Abstract
We examined the extent to which emerging adults engage in different behaviors on Instagram, a popular social networking site, to gain attention and validation from others via “likes.” We also examined individual differences in the frequency of like-seeking behavior and motives for Instagram use as mediators of these relationships. Participants (N = 198 and 265 (replication study)) were recruited via an online crowdsourcing portal to complete a survey. Results demonstrated that, as predicted, participants engaged in an assortment of different like-seeking behaviors. Further, a two-factor solution emerged, with like-seeking behavior separated by whether they were normative (i.e., common or accepted, e.g., using filters or hashtags) or deceptive (e.g., buying likes or changing one’s appearance in photos using software). Deceptive like-seeking was predicted by stronger narcissism and a weaker sense of peer belonging, whereas normative like-seeking was predicted by stronger narcissism and a stronger sense of peer belonging. Further, consistent with hypotheses, significant mediators of the relation between narcissism and deceptive like-seeking included motives to use Instagram to increase popularity and showcase creativity. Results help to identify young people who are more susceptible to engaging in deceptive, potentially harmful acts to gain attention and validation on Instagram.
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A weaker sense of peer belonging among teenagers was positively related to deceptive like-seeking on Instagram.
“Dumas, Maxwell-Smith, Davis, and Giulietti (2017) noted that a weaker sense of peer belonging among teenagers was positively related to deceptive like-seeking on Instagram.”
From Instagram addiction and the Big Five of personality: The mediating role of self-liking (2018) · cites this paper as Dumas, Maxwell-Smith, Davis, and Giulietti (2017)
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“In contrast, young Instagram users are particularly preoccupied with drawing attention and gaining validation from other users, especially via “likes” (Dumas et al., 2017; Lee et al., 2015; Sheldon & Bryant, 2016; Stsiampkouskaya et al., 2021).”
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- Authors
- Dumas, T. M., Maxwell-Smith, M., Davis, J. P., & Giulietti, P. A.
- Affiliations
- Western University (CA)
- University of Illinois Urbana-Champaign (US)
- Corresponding author
- Dumas, Tara M.
- ORCID
- Davis, Jordan P.
- Venue
- Computers in Human Behavior
- Publisher
- Elsevier BV
- Published
- 2017-06
- Volume
- 71
- Pages
- 1-10
- ISSN
- 0747-5632 (ISSN-L)
- OpenAlex
- W2583030325
- Cited by
- 231
- References
- 35
- Citations by year
- 2026: 19 · 2025: 23 · 2024: 27 · 2023: 25 · 2022: 32 · 2021: 30 · 2020: 30 · 2019: 24 · 2018: 20 · 2017: 1
- FWCI
- 52.37
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Computers in Human Behavior (publishedVersion)
- Topics
- Social Sciences › Sociology and Political Science › Impact of Technology on Adolescents
- Social Sciences › Psychology › Clinical Psychology › Personality Traits and Psychology
- Social Sciences › Psychology › Clinical Psychology › Body Image and Dysmorphia Studies
- Keywords
- narcissism, Instagram, peer belonging, loneliness, emerging adulthood, social validation, attention seeking, motivations for social media use
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
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