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Ken Varnum Web Systems Manager University of Michigan Library @varnum
Who Favorited That? Ken Varnum Web Systems Manager University of Michigan Library @varnum
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Overview What are “Favorites”? Brief History & Background
Unified Favorites Usage patterns
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Favorites Ex Libris’ Metalib & Aleph OPAC “My Shelf”
Mirlyn (VuFind-ish) has “favorites” We extended that metaphor into new systems as we built them Then integrated the interfaces & data stores “My Shelf” was one of the few parts of Metalib that was broadly liked and appreciated. We needed to keep it alive, somehow, when we replaced Metalib with our homegrown Summon interface Original VuFind had a favorites tool we didn’t like, so we built our own on top of our social bookmarking tool (may it rest in peace) Summon didn’t have persistent favorites in the native interface; we built our own interface, and added favorites it to several year laters. Kept favorites in the functions of Metalib that we re-created (database finder, journal finder) Integrated because people don’t want to look in different places for their stuff. And some want to organize things.
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Silos Needed a quick replacement for Metalib Expediency
Explore the value
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MLibrary Favorites Interface
Walk through the screen, what’s where, how it works.
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Favorites in Articles (1/4)
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Favorites in Articles (2/4)
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Favorites in Articles (3/4)
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Favorites in Articles (4/4)
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How Many Items Are We Talking About?
Role All Mirlyn Articles Database Journal Metalib Search Faculty 27123 15510 5955 3482 2065 111 Staff 28596 15669 9276 2544 1010 97 Students 33196 19717 10607 1909 938 25 Friends 1738 1482 206 45 1 4 Multiple 148681 62507 61036 19749 4575 814 Total 239334 114885 87080 27729 8589 1051 In the discussion in the following slides, going to focus on people with only one role. Also going to set aside “Metalib Search” items. Data are from item creation through 9/21/2013 Data are tricky; we lost creation dates when we upgraded to Drupal 7 in January Before that, were Mirlyn: 88838 There are about 240,000 items (as of 9/21/2013) Roughly 100,000 migrated into unified favorites 170,000 in system when we went to Drupal 7 65,000 added since 1/29/2013 Articles: 73270 Journals: 5820 Databases: 1615 Saved searches: 1037
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Summary of All Use Number of unique users Unique users by role Faculty
Student Staff Friend
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Items Saved per User Everyone – including people with multiple roles (hard to tease multiple roles out of the data) n = 29375
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Items Saved per Faculty User
Includes librarians n = 2421
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Items Saved per Student User
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Items Saved per Staff User
Includes non-librarian library employees n = 2596
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Usage Compared to Campus Population
U-M Population Favorite Users % of Population Faculty 7,500 1,726 23.0% Staff 36,500 2,596 7.1% Students 54,500 4,193 7.7%
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Usage by Campus Role Role % of Campus Population % of Favorites Usage
Faculty 23.0% 30.5% Staff 7.1% 32.1% Students 7.7% 37.4% Campus population figures from
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40 /60 Rule 40 percent of users have 1 item 60 percent have the rest
Role % w/1 Favorite % w/2+ Favorites Faculty (n = 2421) 35% 65% Staff (n = 2596) 31% 69% Students (n = 4193) 32% 68% All * (n = 29375) 39% 61% * Includes users with multiple roles.
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Campus Role & Favorites Category
Mirlyn Items Articles Items Database Items Journal Items Faculty ~23% 30.5% 23.0% 43.9% 51.5% Staff ~30% 30.8% 35.9% 32.1% 25.2% Students ~8% 38.7% 41.1% 24.1% 23.4% Percentages in left refer to percent of Favorites users
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Course Tags Students and Faculty have one-click add
4888 items with course tags Role(s) Items with Course Tags Items Total % Course-Tagged Items Faculty 337 2421 13.9% Staff 563 2596 21.7% Student 1428 4193 34.1% Multiple 2560 20165 12.7% All 4888 29375 16.6%
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Students’ Use of Course Tags
Category Items w/Course Tags % of Items w/Course Tags % of Course-Tagged Items Total Items Saved by Students Mirlyn 604 3.1% 45.8% 19717 ArticlesPlus 687 6.5% 52.1% 10607 Databases 6 0.3% 0.5% 1909 Journals 21 2.2% 1.6% 938 Total 1318 4.0% 100.0% 33171 Ignoring 25 Search Tools items.
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Conclusions Course tag use underwhelming Favorites use overall
No obvious value to students Plan to build functionality around course tags Favorites use overall Feels to slanted to one-and-done users Data not sufficiently dense Need to combine with broader use analysis
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Acknowledgements Albert Bertram for data extraction
Justin Joque for data analysis advice
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Ken Varnum varnum@umich.edu
Thanks Ken Varnum Happy to answer any questions.
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