Ian Cero, Silverman Award Winner, chats with #SPSM about his research on associative networks for suicide related posts on Twitter, 4/8/18, 9pCT.
Check out this nifty abstract:
“Networks in which similar individuals are more likely to associate with one another than their dissimilar counterparts are called assortative. The clustering of suicides in time and space implies such fatalities likely have assortative features, and suggests other forms of suicide-related behavior may as well. The assortativity of suicide-related verbalizations (SRV) was examined by machine coding 64 million posts from 17 million users of a large social media platform over two 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 SRV was significantly more assortative than chance, up to at least six degrees of separation. When mood was controlled, SRV assortativity remained significantly higher than chance through two degrees of separation, indicating this effect was not just an artifact of mood. Discussion demonstrates how exploiting assortative patterns can improve the efficiency of suicide risk detection.”
So, why is this? And what does this mean (or not), functionally? Let’s talk about that!
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Ian Cero, MA, MPS received his BA in philosophy from Concordia College in 2010, his MA in Clinical Psychology from Minnesota State University in 2012, and worked as a Research Coordinator at the Minneapolis VA Medical Center before coming to Auburn in 2012. Ian is currently completing his internship at the Charleston Consortium Psychology Internship Training Program. He also recently graduated from AU’s Probability and Statistics Masters program, which he completed concurrently with his doctoral studies. Ian’s research interests focus on non-linear models of suicide risk and their application to suicide prevention.