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Nicole Ellison ICWSM 2010 "Researching Interaction in Social Media"

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Nicole Ellison talk at ICWSM - Researching interaction in social media: Examining online and offline communication processes in online dating & social network sites

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Nicole Ellison ICWSM 2010 "Researching Interaction in Social Media"

  1. 1. Nicole  Ellison   Telecommunication,  Information  Studies  &  Media   Michigan  State  University  
  2. 2. • Because  user  perceptions  can  be  important.   • Because  offline  activity  is  often  not  evident  in  online  data.   • Because  user-­‐generated  data  has  biases.  
  3. 3.   How  do  communication  technologies   reshape  how  we  form,  maintain,  and  access   our  social  relationships?     Two  primary  research  contexts:  social  network   sites  and  online  dating    
  4. 4.   RQ:  Does  Facebook  use  play  a  role  in   enabling  individuals  to  accrue  and  maintain   social  capital?       Yes  (Ellison  et  al.,  2007;  Burke  et  al.,  2010;  others)     RQ:  What  online  and  offline  communication   patterns  are  associated  with  Facebook  use  –   and  what  are  their  social  capital  implications?   Does  the  quality  and  quantity  of  “Friends”   matter?    
  5. 5.   “connections  among   individuals  -­‐  social  networks   and  the  norms  of  reciprocity   and  trustworthiness  that   arise  from  them”  (Putnam,   2000)     Putnam  distinguishes   between  bridging    and   bonding  social  capital  
  6. 6.  reflects  strong  ties  with  family  and  close   friends,  who  might  be  in  a  position  to  provide   emotional  support  or  access  to  scarce   resources  
  7. 7.  is  linked  to  “weak  ties”  (Granovetter,  1982),   loose  connections  who  may  provide  useful,   novel  information  or  new  perspectives  for   one  another  (but  typically  not  emotional   support)    “…  technologies  that  expand  one’s  social  network   will  primarily  result  in  an  increase  in  available   information  and  opportunities  —  the  benefits  of  a   large,  heterogeneous  network”  (Donath  &  boyd,   2004).    
  8. 8. •  Surveys   –  August,  2005:  series  of  items  in  survey  given  to  entire  incoming  first-­‐ year  class  at  MSU  (N=1440)   –  April,  2006:  random  sample  of  MSU  undergraduates  (N=286)   –  April,  2007:  participants  from  2005  survey  (N=94)  plus  new  random   sample  (N=482)     –  April,  2008:  new  random  sample  (N=450)  and  panel  data   –  April,  2009:  new  random  sample  (N=373)  and  panel  data   –  April,  2010:  new  random  sample  and  panel  data   •  Interviews  and  cognitive  walk-­‐throughs   –  Spring,  2007:  Focus  on  FB  “Friendship”  (N=18)   –  Spring,  2010:  Focus  on  adult  FB  users  and  info-­‐seeking  (N=18)   •  Automated  capture  of  web  content   –  Spring,  2006:  Periodic  downloads  of  the  MSU  Facebook  site  
  9. 9.   What  are  the  communication  practices  that   Facebook  users  are  engaging  in?     “Meeting  new  people”  vs  maintaining  old  ties     Are  some  Facebook-­‐enabled  communication   strategies  more  productive  than  others?       Are  some  friends  more  helpful  than  others?    
  10. 10.   Total  stranger:  “Imagine  a  [university]  student   you've  never  met  in  real  life  or  had  a  face-­‐to-­‐ face  conversation  with.”     Someone  from  your  residence  hall  (latent  tie):   “Imagine  someone  at  [university]  who  lives  in   your  residence  hall  who  you  would  recognize   but  have  never  spoken  to.”     Close  Friend:  “Think  about  one  of  your  close   friends.”  
  11. 11.   I  use  Facebook  to  meet  new  people.     Total  stranger:  Browse  their  profile  on   Facebook     Total  stranger:  Contact  them  using  Facebook,   or  by  using  information  from  Facebook     Total  stranger:  Add  them  as  a  Facebook   friend     Total  stranger:  Meet  them  face-­‐to-­‐face  
  12. 12.   Close  friend:  Browse  their  profile  on   Facebook     Close  friend:  Contact  them  using  Facebook,   or  by  using  information  from  Facebook     Close  friend:  Add  them  as  a  Facebook  friend     Close  friend:  Meet  them  face-­‐to-­‐face  
  13. 13.   I  have  used  Facebook  to  check  out  someone  I   met  socially.       I  use  Facebook  to  learn  more  about  other  people   in  my  classes.       I  use  Facebook  to  learn  more  about  other  people   living  near  me.       Imagine  someone  at  X  University  who  lives  in   your  residence  hall  who  you  would  recognize  but   have  never  spoken  to.  How  likely  are  you  to   browse  their  profile  on  Facebook?  
  14. 14.   “Approximately  how  many  TOTAL  Facebook   friends  do  you  have  at  [university]  or   elsewhere?”     Median:  300     “Approximately  how  many  of  your  TOTAL   friends  do  you  consider  actual  friends?”     Median:  75  (25%)  
  15. 15.   I  feel  I  am  part  of  the  [X]  University  community     Interacting  with  people  at  [X]  makes  me  want   to  try  new  things     Interacting  with  people  at  [X]  makes  me  feel   like  a  part  of  a  larger  community     I  am  willing  to  spend  time  to  support  general   [X]  activities     At  [X],  I  come  into  contact  with  new  people  all   the  time     Interacting  with  people  at  [X]  reminds  me  that   everyone  in  the  world  is  connected  
  16. 16.   There  are  several  people  at    [X]  I  trust  to  solve   my  problems.     If  I  needed  an  emergency  loan  of  $100,  I  know   someone  at    [X]  I  can  turn  to.     There  is  someone  at    [X]  I  can  turn  to  for  advice   about  making  very  important  decisions.     The  people  I  interact  with  at    [X]  would  be  good   job  references  for  me.     I  do  not  know  people  at    [X]  well  enough  to  get   them  to  do  anything  important.  (Reversed)  
  17. 17.   Year  in  school,  daily  Internet  hours,  self   esteem,  minutes  on  Facebook     Total  Friends  on  Facebook     Actual  friends  on  Facebook     Actual  friends  on  Facebook  (squared  term)     Social  Information-­‐seeking     Adj.  R2  Without  Information-­‐Seeking:  .14     Adj  R2  With  Information-­‐Seeking:  .18  
  18. 18.   Year  in  school*,  daily  Internet  hours,  self   esteem***,  minutes  on  Facebook     Total  Friends  on  Facebook     Actual  friends  on  Facebook***     Actual  friends  on  Facebook  (squared  term)*     Social  Information-­‐seeking***     *:  p<.05     ***:p<.0001  
  19. 19.   Year  in  school,  daily  Internet  hours,  self   esteem,  minutes  on  Facebook     Total  Friends  on  Facebook     Actual  friends  on  Facebook     Actual  friends  on  Facebook  (squared  term)     Social  Information-­‐seeking     Adj.  R2  Without  Information-­‐Seeking:  .09     Adj  R2  With  Information-­‐Seeking:  .11  
  20. 20.   Year  in  school,  daily  Internet  hours,  self   esteem***,  minutes  on  Facebook     Total  Friends  on  Facebook     Actual  friends  on  Facebook***     Actual  friends  on  Facebook  (squared  term)*     Social  Information-­‐seeking***     *:  p<.05     ***:p<.0001  
  21. 21.   Different  SNS  communication  practices   (‘connection  strategies’)  exist  and  have   different  implications  for  social  capital  levels     Of  the  three  (Maintaining,  Initiating,  &  Social   Information-­‐Seeking),  only  Social  Information-­‐ seeking  significantly  predicts  social  capital  levels.     Users  distinguish  between  Facebook  Friends   and  “actual”  friends  on  the  site;  only  “actual”   friends  impact  perceptions  of  social  capital   (curvilinear  relationship)  
  22. 22.   Participants  are  using  the  site  to  learn  more   about  the  people  around  them.       This  information  can  be  used  to  find  common   ground,  lower  barriers  to  interaction,  guide   conversations  to  socially  relevant  topics     Extends  notions  of  latent  ties  (Haythornthwaite,   2005):  Facebook  provides  not  only  the  technical   ability  to  connect,  but  also  the  personal  social   context  that  can  make  these  interactions   socially  relevant  (vs  digital  “crank  calling”)      
  23. 23.   Friends  vs  Actual  Friends     Friends  who  are  not  considered  actual  friends  are   less  likely  to  provide  social  capital  benefits       Actual  Friends  are  productive  –  but  only  to  a  point     SNSs  as  a  proxy  for  proximity?     Identity  information/self-­‐expression  (profile)     Bring  together  those  with  shared  interests     More  communication  opportunities  
  24. 24.   User  perceptions  are  important.     Actual  vs  all  Friends:  All  Friends  are  not  equal.     Perceptions  of  social  capital     Offline  activity  is  often  not  evident  in  online   data.     Social  information-­‐seeking  (an  important   predictor  of  social  capital):  using  the  site  to  find   out  more  about  those  with  whom  users  have  a   minimal  offline  connection  with.  Online  profile   information  can  facilitate  offline  interactions.    
  25. 25.   Unlike  other  forms  of  CMC,  anticipated  future   face-­‐to-­‐face  interaction  is  expected  and   highly  salient.       How  do  online  daters  negotiate  their  desire   to  engage  in  selective  self-­‐presentation  with   their  need  to  present  an  authentic  self?     To  what  extent  do  online  data  represent   offline  characteristics?     Ground  truth  regarding  deception  in  this  context.  
  26. 26.   Interviewed  34  online  daters  about  online   self-­‐presentation  &  impression  formation     Small  cues  matter  (e.g.,  spelling,  timing  of  email)     Need  to  balance  desirability  and  accuracy   ▪  One  strategy:  Portraying  one’s  ‘Ideal  Self’     ▪  “I  think  they  may  not  have  tried  to  lie;  they  just  have   perceived  themselves  differently  because  they  write   about  the  person  they  want  to  be...In  their  profile  they   write  about  their  dreams  as  if  they  are  reality.”     Establishing  credibility  (Show,  don’t  tell)  
  27. 27. •   Investigated  the  extent  to  which  online   dating  profiles  accurately  represented  offline   characteristics  (establishing  “ground  truth”)   •  Methods  notes:   •  Data  collection  took  place  in  NYC   •  80  (heterosexual)  participants,  40  male/40  female   •  Paid  $30  incentive  to  participate  in  a  study  on   “Self-­‐Presentation  in  Online  Dating”  
  28. 28.   Appear  attractive     Reduced  cues;  editable;  asynchronous  (Walther,  ‘96)  
  29. 29.   Appear  attractive     Reduced  cues;  editable;  asynchronous  (Walther,  ‘96)     Appear  honest     Anticipated  future  interaction;  recordability  of  profile   http://www.flickr.com/photos/willie_901/2197990074/
  30. 30.   Appear  attractive    Lie  Frequently     Appear  honest    Lie  Subtly  
  31. 31. Profile-­‐based   Self-­‐Presentation   Observed   Self-­‐Presentation   In  lab  measure:   Cross-­‐Validation   Height   Age   Weight   Income   Photograph  
  32. 32. Overall! Males! Females! Lied about height! 48.10! 55.30! 41.50! Lied about weight! 59.70! 60.50! 59.00! Lied about age! 18.70! 24.30! 13.20! Lied in any category! 81.30! 87.20! 75.60! % Participants Providing Deceptive Information
  33. 33. shorter in reality than profile info shorter in reality than profile info taller in reality than profile info taller in reality than profile info Height
  34. 34. Female Male Lighter in reality than profile info lighter in reality than profile info heavier in reality than profile info Heavier in reality than profile info Weight
  35. 35. younger in reality than profile info younger in reality than profile info older than profile info older in reality than profile info Female Male Age
  36. 36.   Appear  attractive    Lie  Frequently      81%  of  participants  lied  at  least  once      weight  most  frequently,  age  least     Appear  honest    Lie  Subtly    Small  magnitude  for  most  lies      1  –  5%  deviations  from  actual  self    But  there  were  a  few  whoppers!    3  inches;  35  pounds;  9  years    
  37. 37.   User-­‐generated  data  has  biases     Some  are  predictable;  others  are  not.     Multiple  methods  may  be  needed  to  understand  a   particular  online  context     ▪  Technical  constraints  &  affordances,  participants’  goals,   site  norms,  etc.     Understanding  a  particular  social  context  is   critical  for  knowing  how  to  interpret  data   produced  by  its  participants.    
  38. 38.   How  do  online  dating  participants  determine   what  kinds  of  misrepresentations  are   acceptable  and  which  are  unacceptable  (lies)?  
  39. 39.   “For  the  most  part  people  give  a  fairly  accurate   description  of  themselves.  They  might  have  a  little   leeway  here  and  there  like  I  do.  …  I  kind  of  expect   that,  you  know,  they’ll  say  “I’m  35”  and  in  fact   they’re  39.  I  mean  if  they  don’t  look  the  difference,   what’s  the  big  deal  to  me?  It’s  not  skin  off  my  nose.   If  they’re  19  and  they  say  they’re  29  then  I’ve  got  a   problem  with  that....  If  you  misrepresent  to  the   point  where  it’s  going  to  be  a  problem  in  the   relationship,  that’s  not  acceptable.  If  you’re  just   fudging  to  get  over  the  hump,  so  to  speak,  OK,  it’s   ‘no  harm  no  foul.’    
  40. 40. • Because  user  perceptions  can  be  important.   • Because  offline  activity  is  often  not  evident  in  online  data.   • Because  user-­‐generated  data  has  biases.  
  41. 41. • email:  nellison@msu.edu   • papers:    https://www.msu.edu/~nellison/pubs.html   • thanks  to  collaborators  and  co-­‐authors  (in  order  of   appearance):  jennifer  gibbs,  rebecca  heino,  chip   steinfield,  cliff  lampe,  jeff  hancock,  catalina  toma,   danah  boyd,  &  jessica  vitak.  

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