Twitter: Helpful or Hassle?

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An overview of an ongoing study on the effectiveness of Twitter use in academic libraries in the U.S.

Notes from presentation available at http://www.abbybedford.com/static/docs/TechTrendsPresentationNotes.pdf

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Twitter: Helpful or Hassle?

  1. 1. TWITTERhelpful or hassle? Abby Bedford, MSI
  2. 2. Why do astudy about Twitter?
  3. 3. “The library world hasbeen far too gullible,far too willing to regard “any technical advanceas a service advance[.] Lauer, J. D., & McKinzie, S. (2002/2003). Bad moon rising: A candid examination of digital reference and what it means to the profession. Reference Librarian, 38(79/80), 45-56.
  4. 4. Assessment
  5. 5. Literature
  6. 6. Ownership
  7. 7. Question
  8. 8. Are academic libraries in the United States reaching who theythink they are reaching via Twitter?
  9. 9. Study Design
  10. 10. • Get IRB approval
  11. 11. • Get IRB approval - This EXEMPT research protocol has been approved by the Human Research Review Committee at Grand Valley State University. File No. 11-156-H.
  12. 12. • Get IRB approval - This EXEMPT research protocol has been approved by the Human Research Review Committee at Grand Valley State University. File No. 11-156-H.• Identify U.S. academic libraries with Twitter accounts
  13. 13. • Get IRB approval - This EXEMPT research protocol has been approved by the Human Research Review Committee at Grand Valley State University. File No. 11-156-H.• Identify U.S. academic libraries with Twitter accounts• Send these libraries a survey
  14. 14. • Get IRB approval - This EXEMPT research protocol has been approved by the Human Research Review Committee at Grand Valley State University. File No. 11-156-H.• Identify U.S. academic libraries with Twitter accounts• Send these libraries a survey• Code followers of the libraries that answer the survey
  15. 15. • Get IRB approval - This EXEMPT research protocol has been approved by the Human Research Review Committee at Grand Valley State University. File No. 11-156-H.• Identify U.S. academic libraries with Twitter accounts• Send these libraries a survey• Code followers of the libraries that answer the survey• Analyze data
  16. 16. Methodology
  17. 17. Identification
  18. 18. @researchinglib
  19. 19. 485
  20. 20. Survey
  21. 21. via emailvia Twitter
  22. 22. 113
  23. 23. Sample
  24. 24. • targeting students specifically, university at large, or both• currently active Twitter account
  25. 25. 111
  26. 26. •ANOVA (analysis of variance)• 2 degrees of freedom
  27. 27. Cohen, J. (1992). A power primer. Psychological Bulletin, 112, 155-159.
  28. 28. 64
  29. 29. Data
  30. 30. 1 - alumni/major/undergrad2 - professor4 - librarian/library/archivist7 - [blank]
  31. 31. site:http://matthew.reidsrow.com/ projects/tweeps/ code:https://github.com/mreidsma/ tweepgrabber
  32. 32. 1. Students/Alumni2. Faculty/Staff3. University Entity4. Library/Librarian/Library Assn./Library Vendor5. Local Business6. Unaffiliated7. Unknown
  33. 33. 1. Students/Alumni2. Faculty/Staff3. University Entity Affiliated4. Library/Librarian/Library Assn./Library Vendor5. Local Business6. Unaffiliated7. Unknown
  34. 34. 1. Students/Alumni2. Faculty/Staff3. University Entity Affiliated4. Library/Librarian/Library Assn./Library Vendor5. Local Business6. Unaffiliated Unaffiliated7. Unknown
  35. 35. 1. Students/Alumni2. Faculty/Staff3. University Entity Affiliated4. Library/Librarian/Library Assn./Library Vendor5. Local Business6. Unaffiliated Unaffiliated7. Unknown Unknown
  36. 36. PreliminaryResults
  37. 37. average % based on initial coding of 20 libraries
  38. 38. average % based on initial coding of 20 libraries
  39. 39. What’s next?
  40. 40. More coding!
  41. 41. StatisticalAnalysis
  42. 42. DescriptiveAnalysis
  43. 43. Demographics
  44. 44. Conclusions &Recommendations
  45. 45. Write it up.
  46. 46. Breathe
  47. 47. QUESTIONS?
  48. 48. QUESTIONS? Abby Bedford bedforda@gvsu.edu @abby_elizabeth

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