Personal Democracy Forum 2008
Note by David GalielDavid_Galiel:
Ways to draw useful insights from data derived from various social media.
Authors - often post profiles online - geography, posting history,
content time and location - mapping blogging posts over time to reveal national trends
linkages - reciprocal links can be linked similar to social networks
mapping them all can reveal topical clusters
(Question - flashy, 2D or 3D relational maps can reveal patterns and expose relationships in new ways - but, they also tend to hide the underlying biases behind the choices of what to measure and why, where to place nodes, how to spread or clump connections, what is left out entirely/not measured, and the accuracy of measurement. How do we a) expose these underlying decisions when we present relational data in this way, and b) how do we learn to be, and educate others to be, discerning consumers of this kind of data representation?)
Authors - often post profiles online - geography, posting history,
content time and location - mapping blogging posts over time to reveal national trends
linkages - reciprocal links can be linked similar to social networks
mapping them all can reveal topical clusters
(Question - flashy, 2D or 3D relational maps can reveal patterns and expose relationships in new ways - but, they also tend to hide the underlying biases behind the choices of what to measure and why, where to place nodes, how to spread or clump connections, what is left out entirely/not measured, and the accuracy of measurement. How do we a) expose these underlying decisions when we present relational data in this way, and b) how do we learn to be, and educate others to be, discerning consumers of this kind of data representation?)
