Dorm, Major, or Race

“College freshmen are more likely to make friends with peers they share a dorm room or major with than they are to befriend those from similar racial backgrounds…”

I barely remember my roommate from living in the dorm freshman year. He was as much a stranger to me as the person you routinely run into at the store. I felt trapped living on campus when I wanted to be a few miles away in my own bed. His leaving town on weekends to go see his girlfriend was good for me.

My initial declared major was pre-engineering. None of my true friends were also pre-engineering, but then again my true friends were mostly met in high school. The few friends I made in college were all over the place major-wise: pre-law, biology, chemistry, philosophy, english, education, business. They were people I met either in class or at work.

The researchers used Facebook as the measure of who are friends. Given most friendships on Facebook areĀ weak ties rather than strong. The people we know well, trust, and hold great affection reflect our strong ties. The people we barely know, but on whom we depend for the information social networks convey are our weak ties. Facebook is excellent for this. From this perspective, if I were a freshman in college today, I probably would be getting as many people in my classes as I could. (This is why so many of my coworkers are in my list of friends. Don’t worry, Glenn, you are more than just an acquaintance. :))

Night School

I noticed a couple weeks back there are interesting spikes in the evening hours of Sunday through Wednesday. Just like morning/afternoon usage, the evening spikes diminish but even more so by comparison.

As I recall for Monday through Wednesday, when I first started, the evening traffic almost flatlined at 5pm and then dropped off at 11pm. Over time the spike has grown to the point we have more users active in the evening than during “business hours”.

In this graph, the numbers across the bottom are the week of the year. The numbers along the left side are the number of users active within the last 5 minutes.

Yaketystats

Really I have no data to say why the change in trend. (We are not 100% online and the majority of the classes we host are supplemental to face-to-face, with hybrid and totally online fighting for second place.) I hope the days of instructors teaching in a computer lab and having students follow along died a hard painful death. If so, then the amount of activity during the day would lessen some. Students and faculty would still go online during the day between classes. However, more student access to broadband at home would empower them to go online more often in the evening and increase the difference between day and evening user activity.

Identifying where each individual IP resides is hard. Doing so for many is more time than I would want to invest in the question. Campus vs. residential vs. corporate is relatively easy. However, “home” for a student could be on campus or residential. Maybe someone else knows better than me.

I guess this means we really ought to look at our automated operations which kick off at 10pm. WebCT recommended they be run when user activity is light or they could impact performance.