TY - GEN
T1 - Determining the strength of the propensities of a blog network
AU - Yoon, Seok Ho
AU - Kim, Sang Wook
AU - Park, Sunju
PY - 2009
Y1 - 2009
N2 - A blog network, composed of blogs and their relations, may exhibit two different propensities characterized by the purpose of use: an information-oriented propensity and a friendship-oriented propensity. Both propensities coexist in a blog network, and the degree of these propensities may play an important role in business and policy decisions of blog-related business. In this paper, we propose an automated method for determining the propensity values of a blog network. First, classification is used to judge the propensity values of the relation between two blogs. Then, by adding up the propensity values of all the relations in the network, one determines the propensity values of the whole network. Through extensive experiments using a large volume of real-world blog data, we demonstrate our method achieves a high level of accuracy in determining the propensity values of a relation. The results also suggest the applicability of our approach for determining the propensity values of a network.
AB - A blog network, composed of blogs and their relations, may exhibit two different propensities characterized by the purpose of use: an information-oriented propensity and a friendship-oriented propensity. Both propensities coexist in a blog network, and the degree of these propensities may play an important role in business and policy decisions of blog-related business. In this paper, we propose an automated method for determining the propensity values of a blog network. First, classification is used to judge the propensity values of the relation between two blogs. Then, by adding up the propensity values of all the relations in the network, one determines the propensity values of the whole network. Through extensive experiments using a large volume of real-world blog data, we demonstrate our method achieves a high level of accuracy in determining the propensity values of a relation. The results also suggest the applicability of our approach for determining the propensity values of a network.
UR - http://www.scopus.com/inward/record.url?scp=67650501907&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=67650501907&partnerID=8YFLogxK
U2 - 10.1109/CIDM.2009.4938641
DO - 10.1109/CIDM.2009.4938641
M3 - Conference contribution
AN - SCOPUS:67650501907
SN - 9781424427659
T3 - 2009 IEEE Symposium on Computational Intelligence and Data Mining, CIDM 2009 - Proceedings
SP - 140
EP - 145
BT - 2009 IEEE Symposium on Computational Intelligence and Data Mining, CIDM 2009 - Proceedings
T2 - 2009 IEEE Symposium on Computational Intelligence and Data Mining, CIDM 2009
Y2 - 30 March 2009 through 2 April 2009
ER -