2017
DOI: 10.1038/s41562-017-0092
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Connective recovery in social networks after the death of a friend

Abstract: Most individuals have few close friends, leading to potential isolation after a friend's death. Do social networks heal to fill the space left by the loss? We conduct such a study of self-healing and resilience in social networks. We compared de-identified, aggregate counts of monthly interactions in approximately 15,000 Facebook networks in which someone had died with similar friendship networks of living Facebook users. As expected, a substantial amount of social interaction was lost with the death of a frie… Show more

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Cited by 33 publications
(25 citation statements)
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References 38 publications
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“…To see this, the co-occurrence of traits X and Y was treated as an undirected edge in a network, with the weight of each edge equal to the total number of obituaries in which the deceased was described as both X and Y. The resulting networks for each city and the combined network of traits are represented visually in Figures 1,2,3,4,5,6,7,8,9. These visualizations were generated with Gephi, using a standard ForceAtlas layout, adjusting node positions to avoid overlapping labels, and, for more populated networks, attraction distribution to highlight clusters of traits.…”
Section: Resultsmentioning
confidence: 99%
See 1 more Smart Citation
“…To see this, the co-occurrence of traits X and Y was treated as an undirected edge in a network, with the weight of each edge equal to the total number of obituaries in which the deceased was described as both X and Y. The resulting networks for each city and the combined network of traits are represented visually in Figures 1,2,3,4,5,6,7,8,9. These visualizations were generated with Gephi, using a standard ForceAtlas layout, adjusting node positions to avoid overlapping labels, and, for more populated networks, attraction distribution to highlight clusters of traits.…”
Section: Resultsmentioning
confidence: 99%
“…Moreover, praising the dead is a way of performatively identifying with them, which is why Aristotle said of Plato after his death that he was a ''man whom bad men have no right even to praise'' [3]. And recent research on healing in social networks suggests that the death of one member often draws together those who survive [4]. Goethe allegedly observed that we die twice [5]: first when we stop breathing, and again when the last of those who knew and loved us die.…”
Section: Introductionmentioning
confidence: 99%
“…The possibility that the parameters on all social networks (online or offline) are governed by basic underlying factors is further supported by research showing that similar structures also exist within simpler social systems, such as animal societies. For instance, the sizes and scaling of hierarchical “friendship” layers found in online and offline human networks are also found in dolphins, elephants, and various primate species, and the phenomena of humans increasing the number and strength of their social networks connections following the death of a friend on Facebook is also seen in wild birds, which show compensatory up‐regulation of their social network connections upon experiencing the loss of a social associate.…”
Section: Online Social Network: Faulty Connections or False Dichotomy?mentioning
confidence: 99%
“…We may have to look at examples from other social systems to learn about network resilience. The work by Hobbs and Burke [26] is an important step in this direction. They compared how 15,000 Facebook networks behaved in response to the death of a friend.…”
Section: Mass Retirement From a System Resilience Approachmentioning
confidence: 99%
“…They empirically observed network resilience in such groups. Their research on systems of human interactions have demonstrated that networks respond in different manners to crisis situations such as the departure of important agents: forming new temporary connections that dissolve over time, developing new longer-term connections, or; dissolving and possibly becoming dysfunctional [26].…”
Section: Mass Retirement From a System Resilience Approachmentioning
confidence: 99%