What metrics would show change, not confirmation, of readers’ views?

A key question I come back to in various areas, such as publishing/scholarly metrics (“#altmetrics”) and social media design/practice, is how might we detect if and how much a media interaction changes rather than just confirms a reader’s views?

As I noted on Twitter recently:

we gravitate to what doesn’t challenge us, so media metrics (eg pageviews, IF) often reflect & reward #homophily. “Like” makes this explicit

Change-Metrics-tweet

(note:  IF = “Impact Factor,” a standard metric for a scholarly journal’s influence on other scholarship).

This blog post page is to create an anchor and open thread for the topic, and note a few of my efforts to explore it.

First, I have an ongoing project called Diffr about tools to diversity “media diet.” It continues work I did developing a prototype project for the Startup Chile incubator program in Santiago, Chile

DiffrMedia-header

Second, here’s a clip on the topic from a 2012 talk I gave at a Quantified Self Silicon Valley event at Google in Mountain View.  I answer two related questions from the founders of QS, Kevin Kelly and Gary Wolf:

I’m interested to hear anyone’s ideas on this question! Please comment below, or on Twitter (hashtag: #changemetrics), or email tmccormick at gmail..