Citation

Cero I, Witte TK. Am. Psychol. 2019; ePub(ePub): ePub.

Affiliation

Department of Psychology.

Copyright

(Copyright © 2019, American Psychological Association)

DOI

10.1037/amp0000477

PMID

31192621

Abstract

Since the turn of the century, interdisciplinary research on networks-their formation, structure, and influence-has advanced so rapidly, it is now a science unto itself, offering new and powerful quantitative tools for studying human behavior, whose potential psychologists are just beginning to glimpse. Among these tools is a formula for quantifying assortativity, the propensity of similar people to be socially connected with one another more often than their dissimilar counterparts. With this formula, this investigation establishes a foundation for examining assortative patterns in suicidal behavior and highlights how they can be exploited for improved prevention. Specifically, the established clustering of suicide fatalities in time and space implies such fatalities have assortative features. This suggests other forms of suicide-related behavior may as well. Thus, the assortativity of suicide-related verbalizations (SRVs) was examined by machine coding 64 million posts from 17 million users of a large social media platform-Twitter-over 2 distinct 28-day periods. Users were defined as socially linked in the network if they mutually replied to each other at least once.

RESULTS show SRVs were significantly more assortative than chance, through 6 degrees of separation. This implies that if a person posts SRVs, their friends' friends' friends' friends' friends' friends are more likely than chance to do the same even though they have never met. SRVs also remained significantly assortative through 2 degrees, even when mood was controlled.

DISCUSSION illustrates how these assortative patterns can be exploited to improve the true-positive rate of suicide risk screenings. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Language: en