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BEGIN:VEVENT
DTSTAMP:20260309T130109Z
DTSTART:20260507T120000Z
DTEND:20260507T140000Z
SUMMARY:Digital Trust and Security Seminar: Tao Wen
UID:{http://www.columbasystems.com/customers/uom/gpp/eventid/}j1tb-mmj6rt
 tw-x99s25
DESCRIPTION:Explore a series of interconnected studies that examine human
  behavior and decision-making processes within social networks\n\nThis e
 vent invites participants from all disciplines and backgrounds to come t
 ogether\, fostering interdisciplinary connections and discussions.\n\nTa
 lk Title: Modeling and Analyzing User Behavior and Decision-Making in So
 cial Networks\n\nIn today’s digital ecosystem\, social media platforms e
 nable the large-scale and rapid spread of information\, fostering the em
 ergence of collective behaviors while also generating significant societ
 al consequences. These dynamics are reshaping how individuals interact\,
  update beliefs\, and make decisions. This presentation introduces a ser
 ies of interconnected studies that examine human behavior and decision-m
 aking processes within social networks from both theoretical and data-dr
 iven perspectives.\n\nCollective decision-making: We propose a comprehen
 sive framework that models the holistic processes of belief updating and
  decision-making\, shifting the analytical focus from isolated individua
 ls to socially embedded decision-makers. A modified naming game model is
  developed to capture belief dynamics among individuals\, incorporating 
 social learning\, self-learning\, and forgetting mechanisms.\nInfluence 
 maximization: We develop several models\, based on network topology\, mu
 lti-criteria decision-making\, and large language models\, to identify k
 ey users capable of maximizing influence and accelerating information di
 ffusion. These models consistently outperform traditional benchmarks acr
 oss multiple real-world networks.\nSource localization: A novel approach
  that integrates evolutionary computation with generalized Bayesian infe
 rence is introduced to locate the source of information propagation. Thi
 s method achieves superior accuracy and efficiency with minimal prior kn
 owledge about the underlying propagation dynamics or user attributes.\nB
 y illuminating the mechanisms of collective behavior and decision-making
  in an increasingly complex and interconnected digital society\, our wor
 k advances both the theoretical modeling and analytical foundations of h
 uman behavior in networked systems.\n\nRegister here: https://tinyurl.co
 m/4rh59u9s \n\nSpeaker Biography:\n\nTao Wen is currently a Research Fel
 low in AI Trust and Security at Alliance Manchester Business School\, Th
 e University of Manchester. He received his PhD from the Centre for Doct
 oral Training in Data Analytics and Society at The University of Manches
 ter in 2025. His research interests are broadly in the intersection of n
 etwork science\, decision analytics\, data analytics\, and collective dy
 namics.\n\nConnect with the Centre for Digital Trust and Society:\n\nThe
  Centre for Digital Trust and Society organises the DTS Guest Seminar Se
 ries and is a focal point for research across the University of Manchest
 er that explores aspects of trust and security in our digital world. The
  Centre is part of Digital Futures\, a highly interdisciplinary network 
 which operates across the whole range of the University of Manchester's 
 digital research.\n\nAbout Digital Futures:\n\nDigital Futures is a high
 ly interdisciplinary network that operates across the whole range of the
  University’s digital research. We aim to present a coherent overview of
  The University of Manchester's digital research activity to external st
 akeholders and bring together research communities to explore new resear
 ch areas and address strategic opportunities.\n\nConnect with us:\n\nX: 
 twitter.com/DigitalUoM\n\nBlue Sky: bsky.app/profile/digitaluom.bsky.soc
 ial\n\nLinkedin: linkedin.com/showcase/digital-futures-at-the-university
 -of-manchester\n\nWebsite: digitalfutures.manchester.ac.uk\n\nNewsletter
 : tinyurl.com/digitalfuturesuom
STATUS:TENTATIVE
TRANSP:TRANSPARENT
CLASS:PUBLIC
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