The Big Five personality traits, Big Two metatraits and social media: A meta-analysis

Liu, Dong; Campbell, W. Keith

doi:10.1016/j.jrp.2017.08.004

Cited by 177 publications

(147 citation statements)

References 59 publications

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“…For RQ4, while a number of specific associations were found, the strongest associations between online behaviour and personality traits existed between productive and reactive behaviour on Instagram and extroversion. This outcome is indicative of a tendency of extroverted individuals to actively seek out social interaction and supports Liu and Campbell [23] who found that extroversion was the strongest predictor of activity on SNSs. Across both platforms, no associations between online social behaviour and conscientiousness were found.…”

Section: Discussionsupporting

confidence: 80%

“…In addition to the mode of use, evidence suggests that the individual user characteristics (e.g., personality, gender) can influence, firstly, the nature of behaviour online and, secondly, the nature of psycho-social outcomes associated with such behaviour [17,22,37,43]. Extroversion, in particular, has been associated with increased use of SNSs [23].…”

Section: Associations Between Online and Offline Social Behaviourmentioning

confidence: 99%

“…Given the centrality of UISs in life today, the need to understand digital natives' use of UISs, and indications of associations between behaviour online and behaviour offline [28,35,47], the primary objective of this study is to describe patterns of online social behaviour exhibited by digital natives (specifically university students) on two popular SNSs (Facebook and Instagram) and, on this basis, compare their online and offline social behaviour. Additionally, given associations between personality traits and behaviour online [2,23], associations between the well-established Big Five model of personality and online social behaviour are examined.…”

Section: Introductionmentioning

confidence: 99%

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An exploratory investigation of online and offline social behaviour among digital natives

Broughton

Daly

Marx

et al. 2019

Proceedings of the South African Institute of Computer Scientists and Information Technologists 2019

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In response to calls for IS researchers to investigate how digital natives are using information and communication technologies to shape their interpersonal interactions, an exploratory, surveybased study was conducted to investigate patterns of online social behaviour on two popular SNSs (Facebook and Instagram) and, on this basis, compare their online and offline social behaviour. To capture online social behaviour a novel typology involving three high-level interactions -producing, consuming, and reactingwas proposed. The investigation found that, among digital natives, Instagram is used more frequently than Facebook, with consumptive behaviour on Instagram occurring most frequently, and productive behaviour on Facebook occurring least frequently. While online social behaviour was found to positively relate to offline socialisation, personality traits were found to account for a larger proportion of the variance in offline social behaviour than online actions. The findings are of particular relevance to those seeking to understand associations between behaviour online and behaviour offline. Moreover, the typology introduced is likely to be useful in a variety of contexts.

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Section: Discussionsupporting

confidence: 80%

Section: Associations Between Online and Offline Social Behaviourmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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An exploratory investigation of online and offline social behaviour among digital natives

Broughton

Daly

Marx

et al. 2019

Proceedings of the South African Institute of Computer Scientists and Information Technologists 2019

View full text Add to dashboard Cite

show abstract

“…The human brain is multifunctional, capable of task switching from one social media to another in search for good materials to upgrade their knowledge. In fact, social media-use also bring about benefits such as accruing social capital Liu, Ainsworth & Baumeister, 2016;Liu & Compbell, 2017).…”

Section: Discussionmentioning

confidence: 99%

Using technology acceptance model to measure the ese of social media for collaborative learning in Ghana

Amadu

Muhammad

Mohammed

et al. 2018

J. Technol. Sci. Educ.

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In this Digital era, thousands of teens in the universities use social network sites, it has become a way of life. Social Media Usage has recently received numerous debate in its impact on academics, with its advent, communities have become link to each other, but the lecture room still remains quite isolated, from other teachers, students, and a host of others who could potentially enhance learning. This study aimed at investigating the impact of social media usage on students’ academic performance through collaborative learning among university students in Ghana. (Based Davis et al,. 1989) Technology Acceptance Model (TAM), a conceptual framework was adopted for the study. To achieve the objectives, a quantitative data analysis method was employed. A total of 200 students were randomly surveyed for the study. Regression analysis revealed that, Interaction with peers, perceived ease of use and perceived usefulness had a significant positive relationship with collaborative learning. Furthermore, results suggested that there exist a significant mediation effects on the relationship between social media usage dimensions and academic performance. TAM does not take into account environment or economic factors that may influence a person’s intention to perform a behavior. The study recommends a clear mobile learning methodologies, rules and policies for integrating student activities on social media into their final grades.

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“…b. Reviews assessing CMC only in relation to personality constructs such as narcissism or the "big five" were excluded (e.g., Gnambs & Appel, 2018;Liu & Campbell, 2017). Personality is reflective of genetic dispositions and is predictive of certain sets of adaptive or dysfunctional behavior (DeYoung, 2015), hence systematically affecting MH.…”

Section: Table Of Contentsmentioning

confidence: 99%

Computer-mediated communication, social media, and mental health: A conceptual and empirical meta-review

Meier¹,

Reinecke²

2020

Preprint

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Computer-mediated communication (CMC), and specifically social media, may affect the mental health (MH) and well-being of its users, for good or bad. Research on this topic has accumulated rapidly, accompanied by controversial public debate and numerous systematic reviews and meta-analyses. Yet, a higher-level integration of the various disparate conceptual and operational approaches to CMC and MH and individual review findings is desperately needed. To this end, we first develop two organizing frameworks that systematize conceptual and operational approaches to CMC and MH. Based on these frameworks, we integrate the literature through a meta-review of 34 reviews and a content analysis of 594 publications. Meta-analytic evidence, overall, suggests a small negative association between social media use and MH. However, effects are complex and depend on the CMC and MH indicators investigated. Based on our conceptual review and the evidence synthesis, we devise an agenda for future research in this interdisciplinary field.

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The Big Five personality traits, Big Two metatraits and social media: A meta-analysis

Cited by 177 publications

References 59 publications

An exploratory investigation of online and offline social behaviour among digital natives

An exploratory investigation of online and offline social behaviour among digital natives

Using technology acceptance model to measure the ese of social media for collaborative learning in Ghana

Computer-mediated communication, social media, and mental health: A conceptual and empirical meta-review

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