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DTSTAMP:20230831T095746Z
LOCATION:Sanada II
DTSTART;TZID=Europe/Stockholm:20230627T173000
DTEND;TZID=Europe/Stockholm:20230627T180000
UID:submissions.pasc-conference.org_PASC23_sess134_msa134@linklings.com
SUMMARY:Modeling Multi-Platform Information Diffusion in Social Media: Dat
 a-Driven Observations
DESCRIPTION:Minisymposium\n\nAdriana Iamnitchi (Maastricht University)\n\n
 Accurately modeling information diffusion within and across social media p
 latforms has many practical applications, such as estimating the size of t
 he audience exposed to a particular narrative or testing intervention tech
 niques for addressing misinformation. However, it turns out that real data
  reveal phenomena that pose significant challenges to modeling: events in 
 the physical world affect in varying ways conversations on different socia
 l media platforms; coordinated influence campaigns may swing discussions i
 n unexpected directions; a platform’s algorithms direct who sees which mes
 sage.  This talk will discuss challenges in modeling social medial activit
 y in various contexts, from political crises to coordinated disinformation
  campaigns.\n\nDomain: Computer Science, Machine Learning, and Applied Mat
 hematics 
\n\nSession Chair: Marie-Christine Sawley (ICES Foundation)
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