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PRODID:-//Columba Systems Ltd//NONSGML CPNG/SpringViewer/ICal Output/3.3-
 M3//EN
VERSION:2.0
CALSCALE:GREGORIAN
METHOD:PUBLISH
BEGIN:VEVENT
DTSTAMP:20260212T100348Z
DTSTART:20260218T160000Z
DTEND:20260218T173000Z
SUMMARY:Mitchell Centre Seminar Series\, Alessandro Lomi (University of I
 talian Switzerland\, Lugano) Modeling Social Networks with Changeable No
 des
UID:{http://www.columbasystems.com/customers/uom/gpp/eventid/}z17x-mi7jgv
 jo-q2daou
DESCRIPTION:One of the defining features of social networks is that their
  nodes—social agents—are not fixed entities but actively reconfigure the
 ir internal structure in response to changes in their environment. When 
 such reconfiguration occurs\, widely held assumptions about mechanisms o
 f network formation\, such as homophily-based attachment\, become diffic
 ult to interpret. This challenge is particularly evident when network no
 des represent composite or collective actors\, such as formal organizati
 ons\, whose internal structure is itself subject to change. Treating nod
 e identity as fixed therefore limits our ability to understand how trans
 formations in agents and transformations in network structure mutually s
 hape one another over time.\nThis paper addresses this limitation by ref
 raming stochastic actor-oriented models (SAOMs) for mixed-mode networks 
 as a multinomial choice problem in which nodes select among alternative 
 configurations of their internal structure while simultaneously construc
 ting networks of external partners. Relaxing the assumption of stable no
 de identity in this way preserves a coherent account of network dynamics
  while explicitly incorporating endogenous change in node composition. O
 nce internal features of network nodes are allowed to change\, however\,
  standard interpretations of network autocorrelation—the tendency for ti
 es to be patterned by shared\, contextually relevant attributes—require 
 careful reconsideration. This work introduces a new implementation of a 
 widely adopted decomposition of network autocorrelation that explicitly 
 accommodates shifts in the internal composition of nodes.\nUsing data on
  collaborative relations among healthcare organizations\, The empirical 
 analysis shows that this approach captures not only the observed interor
 ganizational network structure\, but also the evolving internal structur
 es of organizations and field-level distributions of activities and reso
 urces. More broadly\, the paper extends stochastic actor oriented models
  to settings in which node identities are endogenous\, enabling the anal
 ysis of coevolving internal structures and network relations.\n\n
STATUS:TENTATIVE
TRANSP:TRANSPARENT
CLASS:PUBLIC
LOCATION:G7\, Humanities Bridgeford Street\, Manchester
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