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SUMMARY:CNN Seminar: Social Networks\, Tie Attributes\, and Channels of Co
 mmunication - Dr Elizabeth Leicht (Saïd Business School in Oxford)
DTSTART:20121120T170000Z
DTEND:20121120T180000Z
UID:TALK42229@talks.cam.ac.uk
CONTACT:Petra Vertes
DESCRIPTION:Technology now mediates a significant fraction of social inter
 actions.  Computational social science is using the large data-sets of use
 r interactions drawn from such communication channels as SMS texts\, mobil
 e phone voice calls\, and online social networks to provide important insi
 ghts into the structure and dynamics of social networks involving thousand
 s or even millions of users. These communication or behavioural based data
 -sets document numerous instances of human interaction\, but information o
 n the real attributes of\, or the actual relationships linking\, interacti
 ng individuals is frequently lacking.  Attribute data has the potential to
  refine our understanding of social interactions that are difficult to qua
 lify based on behavioural data alone.   Using a unique 18-month mobile pho
 ne data-set in combination with supporting self-reported attribute data fr
 om the mobile phone users our work unifies behavioural data studies with m
 ore traditional social network analysis based on survey data.   Our analys
 is reveals the correspondence between social interaction attribute data re
 ported by study participants (ties)\, including the participants' valuatio
 n of tie strength\, with the behavioural interactions occurring via mobile
  phones voice calls and SMS text messages.  We show that variations in per
 ceived social tie strength translate into discernible differences in commu
 nication behaviour via mobile phone voice calls and SMS text messages.  We
  also connect disparities in behavioural data across the two communication
  channels to self-reported tie attributes.
LOCATION:Keynes Hall in Kings College
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