Abstract
A blogosphere is a representative online social network established through blog users and their relationships. Understanding information diffusion is very important in developing successful business strategies for a blogosphere. In this paper, we discuss how to predict information diffusion in a blogosphere. Documents diffused over a blogosphere deal with information on different topics in reality. However, previous studies of information diffusion did not consider the information topic in analysis, which leads to low accuracy in predictions. In this paper, we propose a topic-oriented model to accurately predict information diffusion in a blogosphere. We also define four primary factors associated with topic-oriented diffusion, and propose a method to assign a diffusion probability between blog users for each topic by using regression analysis based on these four factors. Finally, we show the effectiveness of the proposed model through a series of experiments.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Blogger.com Co., Ltd., http://blogger.com
MySpace Co., Ltd., http://www.myspace.com
NHN Co., Ltd., http://blog.naver.com
Daum Co., Ltd., http://blog.daum.com
SK Communications Co., Ltd., http://www.cyworld.com
Lim, S., Kim, S., Park, S., Lee, J.: Determining Content Power Users in a Blog Network: An Approach and Its Applications. IEEE Transactions on Systems, Man, and Cybernetics PART A 41(5), 853–862 (2011)
Kempe, D., Kleinberg, J., Tardos, É.: Maximizing the Spread of Influence Through a Social Network. In: Proc. ACM Int’l. Conf. on Knowledge Discovery and Data Mining, ACM SIGKDD, pp. 137–146 (2003)
Granovetter, M.: Threshold Models of Collective Behavior. American Journal of Sociology, AJS 86(6), 1420–1443 (1978)
Ellison, G.: Learning, Local Interaction, and Coordination. Econometrica: Journal of the Econometric Society 61(5), 1047–1071 (1993)
Chiang, C.L.: Statistical Methods of Analysis, p. 274. World Scientific (2003) ISBN 9812383107
Yoon, S., Shin, J., Park, S., Kim, S.: Extraction of a Latent Blog Community Based on Subject. In: Proc. ACM Int’l Conf. on Information and Knowledge Management, pp. 1529–1532 (2009)
Baeza-Yates, R., Ribeiro-Neto, B.: Modern Information Retrieval, pp. 75–84. ACM Press (1999)
van Rjisbergen, C.J.: Information Retrieval. Butterworth-Heinemann (1979)
Li, X., Wang, Y.-Y., Acero, A.: Learning query intent from regularized click graphs. In: Proc. ACM Int’l. Conf. on Research and Development in Information Retrieval, ACM SIGIR, pp. 344–345 (2008)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Kang, KH., Lim, SH., Kim, SW., Jang, MH., Jeong, BS. (2012). A Topic-Oriented Analysis of Information Diffusion in a Blogosphere. In: Liddle, S.W., Schewe, KD., Tjoa, A.M., Zhou, X. (eds) Database and Expert Systems Applications. DEXA 2012. Lecture Notes in Computer Science, vol 7447. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32597-7_12
Download citation
DOI: https://doi.org/10.1007/978-3-642-32597-7_12
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-32596-0
Online ISBN: 978-3-642-32597-7
eBook Packages: Computer ScienceComputer Science (R0)