I’ve been thinking a lot lately about “social filtering”, or the practice of discovering information by paying attention to what others are paying attention to. Evidence of the attention of others is explicitly captured and aggregated by various social media applications like Digg, delicious, and Twitter / TweetMeme. This is hardly a new concept (see “Edit wear and read wear“, Hill et al., CHI 1992); however, rather than tracking passive traces of use, these applications collect and aggregate explicit actions—posting a link to delicious or Twitter is essentially a user endorsement of the content.
I can’t quite put my finger on it yet, but I feel like there’s something fundamentally different about social filtering as a side effect of saving a story or bookmark or reference for oneself, and posting it so that will be broadcast to others.
For example, I have been using Mendeley for the past 6 months as my reference manager, which is both a desktop application and a social media system. Today I received the March newsletter from Mendeley, which pointed out the “Top 10 most read articles on Mendeley published in 2009“. Number one on the list is the following: Alon, Uri (2009). How to Choose a Good Scientific Problem. Molecular cell, 35(6), 726-8. I was intrigued by the title, so I looked up the paper, and came across another by the same author titled, “How to Build a Motivated Research Group“. Both of these papers contain interesting and valuable insights, and I expect that I will return to them multiple times as I progress in my career.
It seems like the primary use case for Mendeley is storing and organizing references, and sharing them with a group of collaborators. The Mendeley Desktop app synchronizes automatically with the server, so the usage data that was aggregated to produce the “Top 10 in 2009″ list is more like the “read wear” of Hill et al. than the active endorsements of Twitter posts. I doubt I follow anyone on Twitter who reads the journal “Molecular Cell”, so I probably would never have come across these papers if I hadn’t seen them in the newsletter email today. Were the Mendeley users who read this paper even aware that their actions might contribute to the information discovery of others? Are these the kind of content items that anyone would choose to post to Twitter?
Endorsements are different from “read wear” in that they require an extra action on the part of the user, beyond reading it or saving it for themselves, to share the content. How does the “read wear” vs. endorsement distinction, as incorporated in a social media system, affect the content available to users via the system?
