Building and breaking social media habits

Bayer, Joseph B.; Anderson, Ian; Tokunaga, Robert S.

doi:10.1016/j.copsyc.2022.101303

Cited by 43 publications

(39 citation statements)

References 66 publications

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“…WAZE is used by drivers sharing functional information about traffic and road conditions, such as by reporting road accidents, hazards, police, etc. [28], and the majority of interviewees (43) stated that they do not use the application to share other information at all. Reasons for this ranged from a lack of interest in sharing to a fear of getting a ticket for using their mobile phone while driving.…”

Section: Resultsmentioning

confidence: 99%

“…What is not controversial is the idea that social media use relies on habits. Bayer et al [ 43 ] for example, review of key studies and themes highlighted how habitual processes underpin a wide range of common uses and problems among users.…”

Section: Discussionmentioning

confidence: 99%

“…Indeed, there are many ways to understand internet, mobile app, or social media use-including habits, or other behavioral mechanisms which don't require harm to be done for the use of an application to fit their definition, may be 'good' or 'bad' for users, or are more neutral than addiction [42][43][44]. Another might be reward-learning or conditioning, or work on deficient self-regulation [45].…”

Section: Discussionmentioning

confidence: 99%

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In WAZE we trust? GPS-based navigation application users’ behavior and patterns of dependency

Laor

Galily²

2022

PLoS ONE

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Functional technological applications have become an integral part of our lives changing our patterns of reasoning and behavior. The current study examines whether, how and why use of WAZE app, a popular GPS-based navigation application, demonstrate behaviors and patterns which resemble those of technological dependency. We conducted semi-structured in-depth interviews with 50 WAZE users. The questions took inspiration from the model of IT addiction, which identifies six behavioral parameters: withdrawal, conflict, mood modification, relapse, tolerance, and saliency. The novelty of the study lies in the evidence of patterns and behaviors which resemble technological dependency on the WAZE app. The findings indicate that WAZE app satisfies users’ needs driven by functionality. Four behavioral characteristics associated with IT addiction are applicable to WAZE users: mood modification, conflict, relapse, and withdrawal. The study concludes that functional technological applications may trigger behavioral indicators of technological addiction.

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Section: Resultsmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

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In WAZE we trust? GPS-based navigation application users’ behavior and patterns of dependency

Laor

Galily²

2022

PLoS ONE

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“…The rapid outbreak of the coronavirus pandemic (COVID-19) had a significant impact on people's everyday life, as restrictive measures were imposed to reduce physical contact to limit the viral transmission [34][35][36][37]. These changes in lifestyle were associated to an increase of the frequency and intensity of individual's engagement in online activities, including social networking use [20,38]. Such an increase has been associated to managing the reduced sense of control, to escaping the anxiety and uncertainty feelings and to being constantly informed about updates and news and maintain peer-to-peer social contact [39,40].…”

Section: Open Accessmentioning

confidence: 99%

Use of social network as a coping strategy for depression among young people during the COVID-19 lockdown: findings from the COMET collaborative study

et al. 2022

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Background Use of social media (SM) has exponentially grown particularly among youths in the past two years, due to COVID-19-related changing lifestyles. Based on the Italian COvid Mental hEalth Trial (COMET), we investigated the association between SM use and depressive symptoms among Italian young adults (aged 18–24). Methods The COMET is a nationwide multi-center cross-sectional study that investigated socio-demographic data, social networking addiction (BSNAS), depression, anxiety, and stress (DASS-21), as well as impulsiveness (BIS-15) and aggressiveness (AQ) in a large sample of youngsters, in order to assess the association between BSNAS and DASS-21 indices. Mediation analyses were performed to evaluate the role of impulsiveness and aggressive personality traits in the association between SM use (SMU) and depression. Results 75.8% of the sample (n = 491) had a problematic SMU. SMU was reduced by high AQ and high DASS-21 scores (F = 42.338, p < 0.001, R2 = 0.207). Mediation analyses showed that SMU negatively predicted depressive symptomatology with the interaction mediated by AQ total (ß = − 0.1075), physical (ß = − 0.207) and anger (ß = − 0.0582), BIS-15 total (ß = − 0.0272) and attentional (ß = − 0.0302). High depressive levels were predicted by high AQ scores, low SMU levels, low verbal and physical AQ, and low attentional BIS-15 (F = 30.322, p < 0.001, R2 = 0.273). Depressive symptomatology negatively predicted SMU with their interaction mediated by AQ total (ß = − 0.1640), verbal (ß = 0.0436) and anger (ß = − 0.0807), BIS-15 total (ß = − 0.0448) and attentional (ß = − 0.0409). Conclusions SMU during the early phases of the COVID-19 pandemic could have a beneficial role in buffering negative consequences linked to social isolation due to quarantine measures, despite this association being mediated by specific personality traits.

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“…Moreover, applications have also become more popular for providing services relating to specific situations using everyday records [3]. For example, people perform many activities that involve recording daily events, such as taking photos with a camera, writing in a diary, and using social network services (SNS) [4][5][6]. Although merely recording events can be useful, it is important to record daily behavior and life, as well as to perform a meaningful analysis of individual patterns and trends.…”

Section: Introductionmentioning

confidence: 99%

Correlation between Human Emotion and Temporal·Spatial Contexts by Analyzing Environmental Factors

Park

Lee

2022

Future Internet

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In this paper, we propose a method for extracting emotional factors through audiovisual quantitative feature analysis from images of the surrounding environment. Nine features were extracted such as time complexity, spatial complexity (horizontal and vertical), color components (hue and saturation), intensity, contrast, sound amplitude, and sound frequency. These nine features were used to infer “pleasant-unpleasant” and “arousal-relaxation” scores through two support vector regressions. First, the inference accuracy for each of the nine features was calculated as a hit ratio to check the distinguishing power of the features. Next, the difference between the position in the two-dimensional emotional plane inferred through SVR and the ground truth determined subjectively by the subject was examined. As a result of the experiment, it was confirmed that the time-complexity feature had the best classification performance, and it was confirmed that the emotion inferred through SVR can be valid when the two-dimensional emotional plane is divided into 3 × 3.

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Building and breaking social media habits

Cited by 43 publications

References 66 publications

In WAZE we trust? GPS-based navigation application users’ behavior and patterns of dependency

In WAZE we trust? GPS-based navigation application users’ behavior and patterns of dependency

Use of social network as a coping strategy for depression among young people during the COVID-19 lockdown: findings from the COMET collaborative study

Correlation between Human Emotion and Temporal·Spatial Contexts by Analyzing Environmental Factors

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