Need fulfillment and experiences on social media: A case on Facebook and WhatsApp
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Whatsapp and other messaging applications make it easier for individuals to communicate more readily and better fulfill the fundamental need for relatedness.
“Whatsapp and other messaging applications make it easier for individuals to communicate more readily and better fulfill the fundamental need for relatedness (Karapanos et al. 2016).”
From Uses and Gratifications of Problematic Social Media Use Among University Students: a Simultaneous Examination of the Big Five of Personality Traits, Social Media Platforms, and Social Media Use Motives (2020) · cites this paper as Karapanos et al. 2016
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- Authors
- Karapanos, E., Teixeira, P., & Gouveia, R.
- Affiliations
- Universidade da Madeira (PT)
- Corresponding author
- Karapanos, Evangelos
- Venue
- Computers in Human Behavior
- Publisher
- Elsevier BV
- Published
- 2016-02
- Volume
- 55
- Pages
- 888-897
- ISSN
- 0747-5632 (ISSN-L)
- OpenAlex
- W2175943870
- Cited by
- 316
- References
- 65
- Citations by year
- 2026: 10 · 2025: 20 · 2024: 30 · 2023: 36 · 2022: 37 · 2021: 62 · 2020: 39 · 2019: 34 · 2018: 23 · 2017: 21 · 2016: 4
- FWCI
- 18.72
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Computers in Human Behavior (publishedVersion)
- Funders
- FCT (PEst-OE/EEI/LA0009/2015)
- Topics
- Physical Sciences › Computer Science › Computer Networks and Communications › Media and Digital Communication
- Social Sciences › Sociology and Political Science › Impact of Technology on Adolescents
- Physical Sciences › Computer Science › Human-Computer Interaction › Innovative Human-Technology Interaction
- Keywords
- social media adoption, need satisfaction, uses and gratifications theory, Facebook, WhatsApp, intimate communication, lifelogging, social media design
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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.
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