A multiscale approach to network event identification using geolocated twitter data

Computing

Volumn 96, Issue 1, 2014, Pages 3-13

  Yang, Chao ^a   Jensen, Ian ^a   Rosen, Paul ^a  

^a UNIVERSITY OF UTAH   (United States)

Author keywords

Big data; Internet; Social network; Twitter; Visualization

Indexed keywords

BIG DATUM; EVENT IDENTIFICATION; LARGE VOLUMES; MULTI-SCALE APPROACHES; MULTIPLE NETWORKS; NETWORK ACTIVITIES; NETWORK USERS; TWITTER;

DATA VISUALIZATION; FLOW VISUALIZATION; INTERNET; VISUALIZATION;

SOCIAL NETWORKING (ONLINE);

EID: 84893654099     PISSN: 0010485X     EISSN: None     Source Type: Journal    
DOI: 10.1007/s00607-013-0285-5     Document Type: Conference Paper

References (19)

1. Brandes U, Nick B (2011) Asymmetric relations in longitudinal social networks. IEEE Trans Vis Comput Graph 17:2283-2290. doi: 10.1109/TVCG.2011.169
2. Cho E, Myers S, Leskovec J (2011) Friendship and mobility: user movement in location-based social networks. In: ACM Knowledge Discovery and Data Mining, pp 1082-1090
3. Cui W, Zhou H, Qu H, Wong P, Li X (2008) Geometry-based edge clustering for graph visualization. IEEE Trans Vis Comput Graph 14(6):1277-1284. doi: 10.1109/TVCG.2008.135
4. Groh G, Hanstein H, Worndl W (2009) Interactively visualizing dynamic social networks with dyson. In: Vis. Inter. to the Soc. and the Sem. http://data.semanticweb.org/workshop/VISSW/2009/paper/main/10
5. Guo D (2009) Flow mapping and multivariate visualization of large spatial interaction data. IEEE Trans. Vis Comput Graph 15(6):1041-4148. doi: 10.1109/TVCG.2009.143
6. Guo D, Chen J, MacEachren A, Liao K (2006) A visualization system for space-time and multivariate patterns (vis-stamp). IEEE Trans Vis Comput Graph 12(6):1461-1474. doi: 10.1109/TVCG.2006.84
7. Guo D, Gahegan M, Maceachren A, Zhou B (2005) Multivariate analysis and geovisualization with an integrated geographic knowledge discovery approach. Cartogr Geogr Inf Sci 32:113-132
8. Heer J, Boyd D (2005) Vizster: visualizing online social networks. In: IEEE InfoVis, pp 32-39
9. Holten D, van Wijk J (2009) Force-directed edge bundling for graph visualization. Comput Graph Forum 28(3):983-990
10. Keim D, Kriege H (1996) Visualization techniques for mining large databases: a comparison. IEEE Trans Knowl Data Eng 8:923-938
11. Luo W, MacEachren A, Yin P, Hardisty F (2011) Spatial-social network visualization for exploratory data analysis. In: Workshop on Location-Based Social Networks, pp 65-68
12. Modest maps. http://www.modestmaps.com/
13. Moody J, Farland DM, Bender-deMoll S (2005) Dynamic network visualization. Am J Sociol 110(4):1206-1241. doi: 10.1086/421509
14. Newman M (2003) Fast algorithm for detecting community structure in networks. Phys Rev E 69. http://arxiv.org/abs/cond-mat/0309508
15. Perer A, Shneiderman B (2006) Balancing systematic and flexible exploration of social networks. IEEE Trans Vis. Comput Graph 12(5):693-700. doi: 10.1109/TVCG.2006.122
16. Phan D, Xiao L, Yeh R, Hanrahan P, Winograd T (2005) Flow map layout. In: IEEE InfoVis, pp 219-224
17. Rae A (2009) From spatial interaction data to spatial interaction information? Geovisualisation and spatial structures of migration from the 2001 UK census. Comput Environ Urban Syst 33(3):161-178. doi: 10.1016/j. compenvurbsys.2009.01.007
18. Reas C, Fry B (2005) Processing.org: a networked context for learning computer programming. In: ACM SIGGRAPH 2005 Web program
19. Shneiderman B, Aris A (2006) Network visualization by semantic substrates. IEEE Trans Vis Comput Graph 12(5)