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Suicide Ideation of Individuals in Online Social Networks

Overview of attention for article published in PLOS ONE, April 2013
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Title
Suicide Ideation of Individuals in Online Social Networks
Published in
PLOS ONE, April 2013
DOI 10.1371/journal.pone.0062262
Pubmed ID
Authors

Naoki Masuda, Issei Kurahashi, Hiroko Onari

Abstract

Suicide explains the largest number of death tolls among Japanese adolescents in their twenties and thirties. Suicide is also a major cause of death for adolescents in many other countries. Although social isolation has been implicated to influence the tendency to suicidal behavior, the impact of social isolation on suicide in the context of explicit social networks of individuals is scarcely explored. To address this question, we examined a large data set obtained from a social networking service dominant in Japan. The social network is composed of a set of friendship ties between pairs of users created by mutual endorsement. We carried out the logistic regression to identify users' characteristics, both related and unrelated to social networks, which contribute to suicide ideation. We defined suicide ideation of a user as the membership to at least one active user-defined community related to suicide. We found that the number of communities to which a user belongs to, the intransitivity (i.e., paucity of triangles including the user), and the fraction of suicidal neighbors in the social network, contributed the most to suicide ideation in this order. Other characteristics including the age and gender contributed little to suicide ideation. We also found qualitatively the same results for depressive symptoms.

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Mendeley readers

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Geographical breakdown

Country Count As %
United Kingdom 2 1%
Japan 2 1%
United States 2 1%
France 1 <1%
Australia 1 <1%
Netherlands 1 <1%
Spain 1 <1%
Portugal 1 <1%
Colombia 1 <1%
Other 1 <1%
Unknown 169 93%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 31 17%
Researcher 21 12%
Student > Bachelor 19 10%
Student > Master 18 10%
Student > Doctoral Student 16 9%
Other 37 20%
Unknown 40 22%
Readers by discipline Count As %
Psychology 45 25%
Computer Science 23 13%
Social Sciences 22 12%
Medicine and Dentistry 18 10%
Nursing and Health Professions 8 4%
Other 22 12%
Unknown 44 24%