Emotions and Digital Well-Being: on Social Media’s Emotional Affordances

Steinert, Steffen; Dennis, Matthew

doi:10.1007/s13347-022-00530-6

Cited by 39 publications

(23 citation statements)

References 63 publications

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“…• How would allowing user choices affect misinformation spreading and polarization at the macro-scale on digital platforms? algorithms could contribute to solving current problems, and be actively designed to foster shortand long-term well-being and flourishing (Steinert & Dennis, 2022). This requires developing visions for digital media and algorithm design -rather than constraining ourselves to those proposed by existing for-profit companies (Bail, 2021;Büchi, 2021).…”

Section: Social Cohesion Nuanced Political Discussion and High Qualit...mentioning

confidence: 99%

Social drivers and algorithmic mechanisms on digital media

Metzler¹,

García²

2022

Preprint

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The fast and barely regulated adoption of algorithms in digital media has raised concerns about their role in well-being both at the individual and collective level. We illustrate digital media as having algorithmic mechanisms that are powered by social drivers, creating a feedback loop that complicates research to disentangle the role of algorithms and already existing social phenomena. Our review of the causal evidence on how algorithms affect well-being, misinformation, and polarization suggests that the role of algorithms for these phenomena is far from straightforward, and that substantial further empirical research is needed. Existing evidence suggests that algorithms mostly reinforce existing social drivers, which stresses the importance of reflecting on algorithms in the larger societal context including individualism, populist politics, and climate change. We present concrete ideas and research questions to improve algorithms on digital platforms and to investigate their role for current problems and potential solutions. Finally, we discuss how the current shift from social media to more algorithmically curated media brings both risks but also opportunities if algorithms are designed with the aim of individual and societal flourishing rather than short-term profit.

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Section: Social Cohesion Nuanced Political Discussion and High Qualit...mentioning

confidence: 99%

Social drivers and algorithmic mechanisms on digital media

Metzler¹,

García²

2022

Preprint

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“…The rapid rise in digitalization (both a product and driver of the spread of global capitalism) and social media over the last 30 years has (1) increased the number (and possible diversity) of mediated social interactants available to an individual, (2) created spaces for anonymous and anomic play and experimentation, and (3) appears to reward word-play and experimentation with likes and shares. In other words, social media technologies (SMTs) have “relational properties […] that are likely to induce an emotional state or emotion-related behavior” (Steinert & Dennis, 2022, p. 12). One such emotion-related behavior is the creation of neo-emotions (Dolin et al, 2021).…”

Section: Situating Neo-emotions In Macro-level Change and Cultural Ev...mentioning

confidence: 99%

Neo-emotions: An Interdisciplinary Research Agenda

Cottingham

2023

Emotion Review

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Emotion research that attends to the cultural dynamics of affective life remains underdeveloped. I outline an agenda for an understudied phenomenon that can orient emotion researchers to the situated, cultural practices of affective life: Neo-emotions. Neo-emotions, when situated within macro-level processes and cultural events, illustrate the constrained yet creative practices that social actors use to address the disconnect between one's emotional vocabulary and dynamic environment. As such, neo-emotions are analytically rich cultural practices that can be empirically explored through sociological, anthropological, historical, and psychological inquiry. I discuss a range of neo-emotions, including doomscrolling, eco-grief, and Black joy, their social antecedents (digitalization, disasters/crises, and social movements) and methodological implications for an interdisciplinary agenda.

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“…Moreover, SNS can in uence users' emotions and their participation in resistance training by sharing targeted information and affecting their reactions to content. [21][22][23]. Simultaneously, the highly interactive nature of SNS, offering users with intuitive and personalized information along with convenient self-monitoring and tracking capabilities, signi cantly contributes to formulating strategies for the implementation of relevant behaviours [24].…”

Section: Introductionmentioning

confidence: 99%

The effect of social networking sites on resistance training behaviour among college students: application of a mixed model based on the theory of planned behaviour

Wei,

Su,

Chen

et al. 2023

Preprint

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Background The purpose of this study is to explore the effect of social networking sites (SNS) on college students’ participation in resistance training, with a specific focus on the mediating role of planning and emotion in bridging the intention-behaviour gap. Methods Three hundred fifty-six college students (215 males and 141 females, with an average age of 21.37 ± 2.40 years) from 17 universities in China who regularly participate in resistance training were surveyed via questionnaires. The data was analysed using the Maximum Likelihood Estimation (MLE) in AMOS 20.0, and the planned behaviour mixed model was tested using a structural equation model. Results Three main findings emerged from the study: 1) SNS had a positive effect on college students' participation in resistance training; 2) Intention and behaviour towards resistance training among college students were influenced by planning and positive emotion as mediators; 3) College students' participation in resistance training is positively affected by rational cognition. Conclusions The mixed model of planned behaviour examines how SNS influences college students' intentions and behaviour toward resistance training. By combining the advantages of rational thinking with basic emotional instincts, this model provides a more accurate prediction of college students' intentions and behaviours in resistance training.

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Emotions and Digital Well-Being: on Social Media’s Emotional Affordances

Cited by 39 publications

References 63 publications

Social drivers and algorithmic mechanisms on digital media

Social drivers and algorithmic mechanisms on digital media

Neo-emotions: An Interdisciplinary Research Agenda

The effect of social networking sites on resistance training behaviour among college students: application of a mixed model based on the theory of planned behaviour

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