minipost
A few years ago I found myself spending far too much time on Twitter .. generally an hour to an hour and a half a day. Time I didn't have. For a month I went cold turkey, but was frustrated as there were a few people I only interacted with on Twitter and, following about 50 people in one of my fields was a good way to learn about new discoveries and papers. I decided to limit my time, aiming for a half hour a day in two or three sessions. One would be devoted to hunting for new papers and the rest of the time would be the water cooler. It's been mostly successful - I'll admit to hours of serious doom scrolling around the January 2021 coup attempt, but generally I'm under my thirty minute a day limit. (I also have one day a week when I try to cut Internet access completely).
With that background I was fascinated to come across a report on some real-world experimentation by a group of about sixty college undergrads - a group known for heavy social media use. Matt Salganik taught Sociology 204: Social Networks at Princeton last Fall. He posted a report on Princeton's Center for Information Technology Policy's Freedom to Tinker blog:
Improving Your Relationship with Social Media May Call for a Targeted Approach
From the introduction:
What students did:
Our class had about 60 students, from a variety of years and majors, and like most Princeton students, many of them were heavy users of several social media platforms. Each of them designed their own treatment and selected an outcome of interest. For example, some students were interested in improving their sleep and others were interested in wasting less time. In addition to these student-specific outcomes, we also had all students track two common outcomes that have been studied by other researchers: subjective well-being and time use changes.
This process of self-experimentation is a bit different from what social scientists normally do. Typically, researchers standardize the treatment, randomly assign treatments to participants, and collect data so that we can compare across participants and treatment groups. In our class, however, each participant was a researcher and designed a unique treatment for themself. Even though this is not standard for research, self-experimentation can be a good way to learn. The treatments students developed fell into three main groups:
Targeted limitation (about 45%). Students in this group restricted – but did not eliminate – their social media use. For example, students in this group did things like stopping TikTok use after 8pm and avoiding the Instagram feed (but still using Instagram for messaging).
Targeted increase (about 15%). In class, we learned about some research that suggests people who use social media actively—rather than passively scrolling—see an improvement in their well-being. So some students committed to increasing their active engagement with social media. For example, students in this group did things like posting 3 times per day on Instagram or direct-messaging at least 3 friends.
Elimination (about 40%). Students in this group eliminated their social media use altogether on one or more apps. Students who designed these treatments did things like delete Instagram or TikTok from their phone, and some actively replaced their social media use with another activity they valued such as reading the news or spending time with friends.
It's worth reading and non-technical. It also offers some advice and techniques in the assignments section if you want to try learning about your own usage. It seems clear that there's a broad spectrum of positive and negative use patterns.