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SUMMARY:Mining Human Behaviors and Performance in Online Platforms
DTSTART:20181119T100000
DTEND:20181119T113000
DTSTAMP:20260603T181023Z
UID:54b65aa88bf12393ed4dbee7122d52abf266a78571a4a460d706d1a6
CATEGORIES:Conferences - Seminars
DESCRIPTION:Anna Sapienza\nHow do users of online platforms behave while f
 ulfilling specific tasks?What are the factors that have a strong impact on
  a user’s performance?Is it possible to engage individuals through gamif
 ication and incentivize them to achieve better performance? In this talk\,
  I will discuss how to model individual behaviors and groups in gamified t
 echno-social environments\, to quantify individuals’ activity and skills
 \, and identify various cues having an impact on their performance. Our pr
 oject focus on data related to some of the most popular multiplayer online
  games\, e.g. Dota 2. Online games are indeed a modern-days natural settin
 g in which we can both model individual behaviors and identify the mechani
 sms that affect users’ performance. First\, I will show how to model ind
 ividual trajectories via a tensor factorization model. Second\, by buildin
 g the underlying social network of players I will present a recommending s
 ystem for teammates. Finally\, I will analyze the impact that factors\, su
 ch as impersonated role\, mental fatigue\, and social ties\, have on playe
 rs’ performance.\n\nAnna Sapienza is a Postdoctoral Research associate a
 t the USC Information Sciences Institute of Marina del Rey\, CA\, USA\, wh
 ere she works in the Machine Intelligence and Data Science group. Anna hol
 ds a Ph.D. in Applied Mathematics from the Polytechnic University of Turin
 \, Italy\, and carried out her Ph.D. studies in collaboration with the Dat
 a Science group of the ISI Foundation of Turin\, Italy. Her research stays
  at the intersection of Data Science\, Network Science\, and Computational
  Social Science. She is particularly interested in the development of meth
 ods to monitor and model human behaviors in online techno-social environme
 nts. 
LOCATION:BC 333 https://plan.epfl.ch/?room=BC333
STATUS:CONFIRMED
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