TY - GEN
T1 - Multi-Scale Characterization of Social Network Dynamics in the Blogosphere
AU - De Choudhury, Munmun
AU - Sundaram, Hari
AU - John, Ajita
AU - Seligmann, Dorée Duncan
N1 - Copyright:
Copyright 2012 Elsevier B.V., All rights reserved.
PY - 2008
Y1 - 2008
N2 - We have developed a computational framework to characterize social network dynamics in the blogosphere at individual, group and community levels. Such characterization could be used by corporations to help drive targeted advertising and to track the moods and sentiments of consumers. We tested our model on a widely read technology blog called Engadget. Our results show that communities transit between states of high and low entropy, depending on sentiments (positive / negative) about external happenings. We also propose an innovative method to establish the utility of the extracted knowledge, by correlating the mined knowledge with an external time series data (the stock market). Our validation results show that the characterized groups exhibit high stock market movement predictability (89%) and removal of 'impactful' groups makes the community less resilient by lowering predictability (26%) and affecting the composition of the groups in the rest of the community.
AB - We have developed a computational framework to characterize social network dynamics in the blogosphere at individual, group and community levels. Such characterization could be used by corporations to help drive targeted advertising and to track the moods and sentiments of consumers. We tested our model on a widely read technology blog called Engadget. Our results show that communities transit between states of high and low entropy, depending on sentiments (positive / negative) about external happenings. We also propose an innovative method to establish the utility of the extracted knowledge, by correlating the mined knowledge with an external time series data (the stock market). Our validation results show that the characterized groups exhibit high stock market movement predictability (89%) and removal of 'impactful' groups makes the community less resilient by lowering predictability (26%) and affecting the composition of the groups in the rest of the community.
KW - Blogosphere
KW - Community
KW - Multi-scale characterization
KW - Social network analysis
KW - Stock market movement
UR - http://www.scopus.com/inward/record.url?scp=70349249904&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=70349249904&partnerID=8YFLogxK
U2 - 10.1145/1458082.1458363
DO - 10.1145/1458082.1458363
M3 - Conference contribution
AN - SCOPUS:70349249904
SN - 9781595939913
T3 - International Conference on Information and Knowledge Management, Proceedings
SP - 1515
EP - 1516
BT - Proceedings of the 17th ACM Conference on Information and Knowledge Management, CIKM'08
T2 - 17th ACM Conference on Information and Knowledge Management, CIKM'08
Y2 - 26 October 2008 through 30 October 2008
ER -