A Multiscale Approach to Network Event Identification using Geolocated Twitter Data

The large volume of data associated with social networks hinders the
unaided user from interpreting network content in real time. This
problem is compounded by the fact that there are limited tools available
for enabling robust visual social network exploration. We present
a network activity visualization using a novel aggregation glyph
called the clyph. The clyph intuitively combines spatial, temporal,
and quantity data about multiple network events. We also present
several case studies where major network events were easily identified
using clyphs, establishing them as a powerful aid for network users
and owners.

Chao Yang, Ian Jensen, and Paul Rosen. A multiscale approach to network event identification using geolocated twitter data. In Proceedings of the First IMC Workshop on Internet Visualization, WIV 2012, November 2012.

@inproceedings{Yang.2012.WIV,
  author = {Chao Yang and Ian Jensen and Paul Rosen},
  title = {A Multiscale Approach to Network Event Identification using Geolocated
	Twitter Data},
  booktitle = {Proceedings of the First IMC Workshop on Internet Visualization},
  year = {2012},
  month = {November},
  series = {WIV 2012},
  abstract = {The large volume of data associated with social networks hinders the
	unaided user from interpreting network content in real time. This
	problem is compounded by the fact that there are limited tools available
	for enabling robust visual social network exploration. We present
	a network activity visualization using a novel aggregation glyph
	called the clyph. The clyph intuitively combines spatial, temporal,
	and quantity data about multiple network events. We also present
	several case studies where major network events were easily identified
	using clyphs, establishing them as a powerful aid for network users
	and owners.},
}