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UID:pretalx-pyconde-pydata-2024-CY97LS@pretalx.com
DTSTART;TZID=CET:20240423T160000
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DESCRIPTION:The COVID-19 pandemic and associated policy measures lead to wo
 rld-wide protest movements that were singled out by the spread of misinfor
 mation and conspiracy theories\, predominantly on social media platforms. 
 Publicly available social media data therefore is a powerful proxy for stu
 dying these protest movements. The data\, consisting of user locations\, f
 ollower relationships\, and content information\, allows to understand the
  geographical centers of activity\, network structure\, and key themes of 
 conspiracy movements.\n\nThis talk will present a multi-dimensional networ
 k analysis for the Austrian COVID-10 protest movement using Python librari
 es like geopandas\, networkx and gensim.\nIn particular\, it will demonstr
 ate how to identify geo-spatial hot spots using spatial statistics\, dense
 ly connected clusters within the network by employing community detection 
 techniques\, as well as dominating content themes through topic modeling a
 pproaches.\n\nThe presentation highlights how data-driven analysis enables
  further understanding of movements that may pose threats to democracy\, a
 longside the importance of publicly available social media data for addres
 sing societal challenges.
DTSTAMP:20260412T002332Z
LOCATION:B07-B08
SUMMARY:Analyzing COVID-19 Protest Movements: A Multidimensional Approach U
 sing Geo-Social Media Data - Umut Nefta Kanilmaz
URL:https://pretalx.com/pyconde-pydata-2024/talk/CY97LS/
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