Effects of social media overload on academic performance: a stressor–strain–outcome perspective

The excessive use of social media is an emerging phenomenon with several negative consequences in an entrepreneurial context. Based on the stressor–strain–outcome paradigm, this research aims to unveil the following: that social media late-night usage can affect two psychological strains (life invasion and technostress) among female entrepreneurs and thus influence their behavioral outcome (cognitive engagement). This study empirically tested the proposed mediation model using an online survey of 225 female entrepreneurs from the small- and medium-sized enterprise sector. A partial least squares structural equation modeling (PLS-SEM) was implemented to obtain the results. The findings indicate that late-night social media usage significantly raises life invasion and technostress among female entrepreneurs. Moreover, internal strains (life invasion and technostress) reduce female entrepreneurs’ cognitive engagement and significantly mediate the association between late-night use of social media and entrepreneurial cognitive engagement. This study draws associated practical and theoretical contributions based on findings, which were not previously discussed.

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Prediction of social media effects on students’ academic performance using Machine Learning Algorithms (MLAs)

Journal of Computers in Education ◽

10.1007/s40692-021-00201-z ◽

2021 ◽

Author(s):

Isaac Kofi Nti ◽

Samuel Akyeramfo-Sam ◽

Bright Bediako-Kyeremeh ◽

Sylvester Agyemang

Keyword(s):

Machine Learning ◽

Social Media ◽

Academic Performance ◽

Media Effects ◽

Learning Algorithms ◽

Machine Learning Algorithms

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The Divergent Roles of Social Media in Adolescents’ Academic Performance

Journal of Research in Childhood Education ◽

10.1080/02568543.2019.1703124 ◽

2020 ◽

Vol 34 (2) ◽

pp. 167-182 ◽

Cited By ~ 1

Author(s):

Jiutong Luo ◽

Luyao Liang ◽

Hui Li

Keyword(s):

Social Media ◽

Academic Performance

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Correlates of social media fatigue and academic performance decrement

Information Technology and People ◽

10.1108/itp-06-2019-0289 ◽

2020 ◽

Vol ahead-of-print (ahead-of-print) ◽

Cited By ~ 5

Author(s):

Aqdas Malik ◽

Amandeep Dhir ◽

Puneet Kaur ◽

Aditya Johri

Keyword(s):

Social Media ◽

Academic Performance ◽

Adult Students ◽

Instant Messaging ◽

Well Being ◽

Online Behavior ◽

Cross Sectional ◽

Self Disclosure ◽

Content Type ◽

Antecedents And Consequences

PurposeThe current study aims to investigate if different measures related to online psychosocial well-being and online behavior correlate with social media fatigue.Design/methodology/approachTo understand the antecedents and consequences of social media fatigue, the stressor-strain-outcome (SSO) framework is applied. The study consists of two cross-sectional surveys that were organized with young-adult students. Study A was conducted with 1,398 WhatsApp users (aged 19 to 27 years), while Study B was organized with 472 WhatsApp users (aged 18 to 23 years).FindingsIntensity of social media use was the strongest predictor of social media fatigue. Online social comparison and self-disclosure were also significant predictors of social media fatigue. The findings also suggest that social media fatigue further contributes to a decrease in academic performance.Originality/valueThis study builds upon the limited yet growing body of literature on a theme highly relevant for scholars, practitioners as well as social media users. The current study focuses on examining different causes of social media fatigue induced through the use of a highly popular mobile instant messaging app, WhatsApp. The SSO framework is applied to explore and establish empirical links between stressors and social media fatigue.

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