The “use” of an electronic resource from a social network analysis perspective

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Presented at QQML 2013: Qualitative and Quantitative Methods in Libraries International Conference. Rome, Italy. …

Presented at QQML 2013: Qualitative and Quantitative Methods in Libraries International Conference. Rome, Italy.

Academic libraries in the United States typically reference proxy server and/or COUNTER statistics to describe the usage of their electronic resources, but we know that a “use” is arguably more than a resource accessed or downloaded. This article employs social network analysis to bridge the typical ways of talking about usage statistics, to provide a context-specific perspective about the mediated use of electronic resources. The article reports on an analysis of data gathered at the Loyola Marymount University (Los Angeles, California) using traditional statistics as well as library reference encounters with patrons during which an electronic resource is mentioned. We use the reference encounters in a social network analysis to examine the relationship between a patron, a librarian, and an electronic resource to more fully describe the use of the resource. This research provides a conceptual model for comparison between traditional COUNTER statistics, proxy server statistics, and the social network analysis perspective. We transform qualitative data into quantitative data in order to develop a grounded theory about the mediated access to library electronic resources.

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  • 1. The  “use”  of  an  electronic  resource  from  a  social  network  analysis  perspective    Marie  R.  Kennedy                                    David  P.  Kennedy  Loyola  Marymount  University                  RAND  Corporation  
  • 2. What  is  a  “use”?  !   An  access  !   A  download  !   A  hit  !   A  search  !   A  session  !   A  save  
  • 3. How  is  a  “use”  counted?  !   COUNTER  “successful  full-­‐text  article  requests”  !   Proxy  server  “hits”  !   Service  desk  transaction  data  via  Gimlet    
  • 4. COUNTER  !   How  the  statistics  are  typically  gathered  !   SUSHI  protocol  assists  in  retrieval  !   Retrieved  to  a  system  that  houses  or  to  single  files  stored  locally  
  • 5. “Both  Project  COUNTER  (Counting  Online  Usage  of  NeTworked  Electronic  Resources)  and  the  Standardized  Usage  Statistics  Harvesting  Initiative  (SUSHI)  of  the  National  Information  Standards  Organization  (NISO)  lack  a  definition  for  a  usage.”  (p.  8  Grogg  and  Fleming-­‐May).    
  • 6. Proxy  server  !   How  the  statistics  are  typically  gathered  !   Typically  a  manual  process  !   Single  files  stored  locally  
  • 7. Gimlet  !   From  hash  marks  on  a  piece  of  scrap  paper,  service  point  transactions  are  now  entered  into  this  commercial  system  !   customizable    
  • 8. Gimlet  at  LMU  !   Manually  entered:  !   Initials  !   Where  the  transaction  took  place  !   Duration  of  the  transaction  !   Format  of  the  transaction    !   Questioner  !   Question  Type  !   Difficulty  !   Question  asked  !   Answer  !   Tags  
  • 9. Gimlet  at  LMU  !   Automatically  entered:  !   Date  !   Day  of  the  week  !   Time  
  • 10. Guiding  question  Can  a  social  network  analysis  of  “usage”  contribute  to  a  deeper  understanding  of  the  use  of  electronic  resources  in  an  academic  setting?  
  • 11. Methods  !   Describe  and  compare  3  kinds  of  measurements  of  electronic  resource  usage  !   June  1,  2011-­‐May  31,  2012  
  • 12. COUNTER  
  • 13. Proxy  server  
  • 14. Social  Network  Analysis  !   Data  extracted  from  Gimlet  !   11,444  total  service  point  interactions  !   4,024  tagged  as  reference  interactions  !   1,548  of  the  reference  interactions  mention  an  electronic  resource  !   Universe  of  electronic  resources  at  LMU  !   194  entries  (58%)  on  the  Research  Databases  page  not  mentioned  once  during  the  year  analyzed  !   137  of  331  resources  mentioned  
  • 15. Social  Network  Analysis  !   New  data  set  created  !   1,548  of  the  reference  interactions  mention  an  electronic  resource  !   Listed  the  resource  mentioned  and  counted  each  time  it  was  suggested  !   Analyzed  and  visualized  using  Ucinet,  Netdraw    
  • 16. Science  Direct  JSTOR   SAGE  Journals  Online  Staff  1   0   4   1  Staff  2   0   1   0  Staff  3   2   0   1  Ucinet  Netdraw  Sample  data  matrix  
  • 17. The  universe  of  electronic  resources  and  Information  Desk  staff  
  • 18. Electronic  resources  and  Information  Desk  staff,  by  color/shape  
  • 19. Benefits  of  using  SNA  !   We  are  provided  new  views  of  the  use  of  electronic  resources,  especially  the  social  component.    !   We  can  see  which  resources  were  not  suggested  over  the  course  of  one  year.  !   We  have  evidence  that  e-­‐resources  are  suggested  and  used  in  concert;  there  are  central  resources  that  are  mentioned  together,  instead  of  a  single  e-­‐resource  resolving  an  information  need.    
  • 20. Type  of  coun+ng  mechanism  Top  5  resources,  from  highest  to  lowest  COUNTER   JSTOR  Academic  Search  Complete  OmniFile  Full  Text  Mega  (H.W.  Wilson)  Science  Direct  SAGE  Journals  Online  proxy  server   ProQuest   EBSCO   LexisNexis   JSTOR  SAGE  Journals  Online  Gimlet  Academic  Search  Complete  JSTOR  Business  Source  Complete  ERIC   ATLA  
  • 21. Type  of  coun+ng  mechanism  Top  5  resources,  from  highest  to  lowest  COUNTER   JSTOR  Academic  Search  Complete  OmniFile  Full  Text  Mega  (H.W.  Wilson)  Science  Direct  SAGE  Journals  Online  proxy  server   ProQuest   EBSCO   LexisNexis   JSTOR  SAGE  Journals  Online  Gimlet  Academic  Search  Complete  JSTOR  Business  Source  Complete  ERIC   ATLA  
  • 22. Future  research  !   Further  analysis  on  existing  data  set  !   Kinds  of  e-­‐resources  suggested  to  kinds  of  patrons  !   Kinds  of  reference  desk  staff  suggest  which  kinds  of  e-­‐resources  !   Expand  data  set  to  include  more  years  of  data  !   Develop  e-­‐resource  marketing  plan  and  look  at  resulting  3  kinds  of  usage  data  
  • 23. Summary  We  find  that  the  perspective  gained  from  social  network  analysis  provides  a  context-­‐aware  component  that  provides  a  fuller  picture  of  the  “use”  of  electronic  resources.    
  • 24. Contact  us  Marie  R.  Kennedy  marie.kennedy@lmu.edu  David  P.  Kennedy  davidk@rand.org  This  presentation  is  supported  by  a  Research  Incentive  Grant  from  the    William  H.  Hannon  Library  at  LMU    
  • 25. Bibliography  !  Bates,  Marcia.  1989.  The  Design  of  Browsing  and  Berrypicking  Techniques  for  the  Online  Search  Interface.  Online  Review,  13(5):  407-­‐424.  ! Borgatti,  S.P.  2002.  Netdraw  Network  Visualization.  Harvard:  Analytic  Technologies.  ! Borgatti,  S.P.,  Everett,  M.G.  and  Freeman,  L.C.  2002.  Ucinet  for  Windows:  Software  for  Social  Network  Analysis.  Harvard:  Analytic  Technologies.  ! Dervin,  Brenda.  1977.  Useful  Theory  for  Librarianship:  Communication,  Not  Information.  Drexel  Library  Quarterly,  13(3):  16-­‐32.  !  Fleming-­‐May,  R.  A.,  &  Grogg,  J.  E.  (2010a).  Assessing  Use  and  Usage:  The  Imperative  (the  concept  of  electronic  resource  usage  and  libraries).  Library  Technology  Reports,  46(6):  5–10.  ! Haythornthwaite,  Caroline.  1996.  Social  Network  Analysis:  An  Approach  and  Technique  for  the  Study  of  Information  Exchange.  LISR,  18:  323-­‐342.  ! Kulthau,  Carol.  1993.  A  Principle  of  Uncertainty  for  Information  Seeking.  Journal  of  Documentation,  49(4):  339-­‐355.  !  Luther,  J.  (2001).  White  Paper  on  Electronic  Journal  Usage  Statistics.  The  Serials  Librarian,  41(2),  119–148.  !  National  Information  Standards  Organization,  The  Standardized  Usage  Statistics  Harvesting  Initiative  (SUSHI)  Protocol,  ANSI/NISO  Z39.93-­‐2013  (Baltimore,  MD:  NISO,  2013).  !  Peters,  Thomas  A.  2002.  What’s  the  Use?  The  Value  of  E-­‐resources  Usage  Statistics.  New  Library  World,  103(1172/1173):  39-­‐47.  ! Talja,  Sanna.  2002.  Information  Sharing  in  Academic  Communities:  Types  and  Levels  of  Collaboration  in  Information  Seeking  and  Use.  New  Review  of  Information  Behaviour  Research,  3:  143-­‐160.  !  Tucker,  Cory.  2009.  Benchmarking  Usage  Statistics  in  Collection  Management  Decisions  for  Serials.  Journal  of  Electronic  Resources  Librarianship,  21:  48-­‐61.  doi:  10.1080/19411260902858581  ! Zheng,  Yanlin,  and  Yoneo  Yano.  2006.  A  framework  of  context-­‐awareness  support  for  peer  recommendation  in  the  e-­‐learning  context.  British  Journal  of  Educational  Technology,  38(2):  197-­‐210.  doi:  10.1111/j.1467-­‐8535.2006.00584.x