A son of EdTechie - if you thought edtechie.net lacked insight.....
11 Jun 13

This one leaves a nasty tang in the mouth

02 May 13
02 May 13

Actually quite a nice video, but wow, it throws some stuff in there

18 Jul 11
24 May 11
In a new study of crowd wisdom — the statistical phenomenon by which individual biases cancel each other out, distilling hundreds or thousands of individual guesses into uncannily accurate average answers — researchers told test participants about their peers’ guesses. As a result, their group insight went awry.
Sharing Information Corrupts Wisdom of Crowds | Wired Science | Wired.com
16 May 11

16 May 11
Social networks tend to disproportionally favor connections between individuals with either similar or dissimilar characteristics. This propensity, referred to as assortative mixing or homophily, is expressed as the correlation between attribute values of nearest neighbour vertices in a graph. Recent results indicate that beyond demographic features such as age, sex and race, even psychological states such as “loneliness” can be assortative in a social network. In spite of the increasing societal importance of online social networks it is unknown whether assortative mixing of psychological states takes place in situations where social ties are mediated solely by online networking services in the absence of physical contact. Here, we show that general happiness or Subjective Well-Being (SWB) of Twitter users, as measured from a 6 month record of their individual tweets, is indeed assortative across the Twitter social network. To our knowledge this is the first result that shows assortative mixing in online networks at the level of SWB. Our results imply that online social networks may be equally subject to the social mechanisms that cause assortative mixing in real social networks and that such assortative mixing takes place at the level of SWB. Given the increasing prevalence of online social networks, their propensity to connect users with similar levels of SWB may be an important instrument in better understanding how both positive and negative sentiments spread through online social ties. Future research may focus on how event-specific mood states can propagate and influence user behavior in “real life”.
[1103.0784] Happiness is assortative in online social networks