Do Facebook Status Updates Reflect Subjective Well-Being?

Liu, Pan; Tov, William; Kosinski, Michal; Stillwell, David; Qiu, Lin

doi:10.1089/cyber.2015.0022

Cited by 67 publications

(49 citation statements)

References 41 publications

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“…Users with suicidal ideation were investigated by 8 studies [30-33,35,39,51,60]. Happiness, satisfaction with life, and well-being were investigated by 7 studies [28,34,47,54, 55,68,71]. …”

Section: Resultsmentioning

confidence: 99%

Researching Mental Health Disorders in the Era of Social Media: Systematic Review

Wongkoblap¹,

Vadillo²,

Ćurčin³

2017

J Med Internet Res

220

164

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BackgroundMental illness is quickly becoming one of the most prevalent public health problems worldwide. Social network platforms, where users can express their emotions, feelings, and thoughts, are a valuable source of data for researching mental health, and techniques based on machine learning are increasingly used for this purpose.ObjectiveThe objective of this review was to explore the scope and limits of cutting-edge techniques that researchers are using for predictive analytics in mental health and to review associated issues, such as ethical concerns, in this area of research.MethodsWe performed a systematic literature review in March 2017, using keywords to search articles on data mining of social network data in the context of common mental health disorders, published between 2010 and March 8, 2017 in medical and computer science journals.ResultsThe initial search returned a total of 5386 articles. Following a careful analysis of the titles, abstracts, and main texts, we selected 48 articles for review. We coded the articles according to key characteristics, techniques used for data collection, data preprocessing, feature extraction, feature selection, model construction, and model verification. The most common analytical method was text analysis, with several studies using different flavors of image analysis and social interaction graph analysis.ConclusionsDespite an increasing number of studies investigating mental health issues using social network data, some common problems persist. Assembling large, high-quality datasets of social media users with mental disorder is problematic, not only due to biases associated with the collection methods, but also with regard to managing consent and selecting appropriate analytics techniques.

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“…Users with suicidal ideation were investigated by 8 studies [30-33,35,39,51,60]. Happiness, satisfaction with life, and well-being were investigated by 7 studies [28,34,47,54, 55,68,71]. …”

Section: Resultsmentioning

confidence: 99%

Researching Mental Health Disorders in the Era of Social Media: Systematic Review

Wongkoblap¹,

Vadillo²,

Ćurčin³

2017

J Med Internet Res

220

164

View full text Add to dashboard Cite

show abstract

“…Traditional psychology methods to track mental well-being include pen and paper surveys, and controlled laboratory observations using a limited number of participants. However, the large penetration of social media sites and smartphones, together with recent advances on mobile sensing technologies, have allowed researchers to conduct studies using unobtrusive methodologies, reaching many more participants [35,10,45]. Although social media technologies have been demonstrated to be useful for tracking users' happiness, they usually show a partial view of peoples' lives: their online life.…”

Section: Introductionmentioning

confidence: 99%

Mobile Sensing at the Service of Mental Well-being

Servia-Rodríguez

Rachuri

Mascolo

et al. 2017

Proceedings of the 26th International Conference on World Wide Web

139

210

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Measuring mental well-being with mobile sensing has been an increasingly active research topic. Pervasiveness of smartphones combined with the convenience of mobile app distribution platforms (e.g., Google Play) provide a tremendous opportunity to reach out to millions of users. However, the studies at the confluence of mental health and mobile sensing have been longitudinally limited, controlled, or confined to a small number of participants. In this paper we report on what we believe is the largest longitudinal in-the-wild study of mood through smartphones. We describe an Android app to collect participants' self-reported moods and system triggered experience sampling data while passively measuring their physical activity, sociability, and mobility via their device's sensors. We report the results of a large-scale analysis of the data collected for about three years from ∼ 18, 000 users.The paper makes three primary contributions. First, we show how we used physical and software sensors in smartphones to automatically and accurately identify routines. Then, we demonstrate the strong correlation between these routines and users' personality, well-being perception, and other psychological variables. Finally, we explore predictability of users' mood using their passive sensing data. Our findings show that, especially for weekends, mobile sensing can be used to predict users' mood with an accuracy of about 70%. These results have the potential to impact the design of future mobile apps for mood/behavior tracking and interventions.

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“…In addition, a positive correlation between poor mental health and frequent use of social networks during developmental age has been evidenced (Sampasa-Kanyinga & Lewis, 2015). Other works have shown a significant interaction between adolescents' well-being, social self-esteem and the use of social networks (Valkenburg, Peter, & Schouten, 2006) as well as a significant correlation between negative emotions and status exhibited on Facebook (Liu, Tov, Kosinski, Stillwell, & Qiu, 2015). Still, Baker & Algorta (2016) founded a non-significant relation between depressive symptoms and use of social networks.…”

Section: Adolescents On Line Identity and Major Risky Online Behavioursmentioning

confidence: 92%

Adolescents’ Online And Offline Identity: A Study On Self-Representation

Cimino¹,

Erriu²,

Pisano³

et al. 2017

European Proceedings of Social &Amp; Behavioural Sciences

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Adolescence represents a crucial period for the construction of personal and social identity. Nowadays, youths create their offline and online identity, as an undistinguishable and complex Self. Adolescents, indeed, construct their online identity as an integration of their physical and virtual persona. This integration might be difficult to represent and communicate to others. The Internet is widely spread among adolescents, and it can favour the development of risky online behaviours, which in turn can involve the occurrence of youth's negative consequences, such as emotional problems, or difficulties in social behaviours. The present study intends to explore, in a sample of Italian adolescents, the capacity of representing the online and offline identity. This capacity is hypothesized to result in an adaptive use of the web. The sample was composed by 200 Italian adolescents, aged 14-17 years, who filled out an adhoc questionnaire tapping different aspects of representation of virtual reality. Adolescents revealed an unclear representation of their virtual identity. Because of their difficulties in identifying the relationship between the real and the virtual identity, the consequences of their activities in the web and in virtual communities are frequently underestimated. Identity and representation of the Self that adolescents express through social networks are very complex topics and the relationship between real and virtual identity needs further research, to carry out effective programs of prevention and intervention of problematic internet use in adolescence.

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Do Facebook Status Updates Reflect Subjective Well-Being?

Cited by 67 publications

References 41 publications

Researching Mental Health Disorders in the Era of Social Media: Systematic Review

Researching Mental Health Disorders in the Era of Social Media: Systematic Review

Mobile Sensing at the Service of Mental Well-being

Adolescents’ Online And Offline Identity: A Study On Self-Representation

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