Users could have multiple affiliations, but these appeared to be designated without a set order (e.g., some users were students^student_worder, others were student_worker^student). We used these in combination with Registrar_School, assigned for students, and Display_Deparment and MBU (major business unit), assigned for employees, to generate a primarily affiliation.
The resulting user affiliation breakdown is:
Affiliation | N (Connections) | Percent | Distinct N (Users) | Distinct Percent |
---|---|---|---|---|
alumni | 54588 | 0% | 253 | 0% |
faculty | 75691 | 1% | 1288 | 4% |
grad | 494082 | 3% | 3554 | 10% |
library | 650492 | 5% | 193 | 0% |
other | 32018 | 0% | 234 | 0% |
staff | 248895 | 2% | 2256 | 6% |
ugrad | 9826989 | 69% | 15452 | 40% |
unknown | 1727 | 0% | 25 | 0% |
NA | 2959401 | 21% | 14930 | 40% |
N (Connections) represents each 1/2 hour for which a user is connected; Distinct N (Users) counts each unique user id only once. Thus, while 69% of the wifi connections across all half-hour increments are for undergraduates, undergraduate students make up 40% of the unique users to the library throughout the year.
Across each academic period, undergraduate students represnet a far higher number of library visitors. Graduate students and University staff (exluding library employees) are the next most common, followed by faculty. Compared to undergraduates, the number of distinct visitors among grad students, staff, and faculty is fairly constant across Fall, Spring, and Summer.
Undergraduate students represent an even higher proportion of Clemons visitors, again with a greater number in the Fall compared to the Spring. Clemons sees about half as many distinct graduate student visitors as Alderman each semeseter.
The following graphs present the number of distinct visitors each month by affilitation in Alderman and in Clemons.
The final set of figures shows the unique undergraduate and graudate student visitors, faculty visitors, and staff visitors to Alderman each day and to Clemons each day. When comparing these graphs, keep in mind that the range of the y-axis is quite different across type of user.