Abstract
Blog mining is an important area of behavior informatics because produces effective techniques for analyzing and understanding human behaviors from social media. In this paper, we propose the blogger-link-topic model for blog mining based on the multiple attributes of blog content, bloggers, and links. In addition, we present a unique blog classification framework that computes the normalized document-topic matrix, which is applied our model to retrieve the classification results. After comparing the results for blog classification on real-world blog data, we find that our blogger-link-topic model outperforms the other techniques in terms of overall precision and recall. This demonstrates that additional information contained in blog-specific attributes can help improve blog classification and retrieval results.
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References
Blei, D.M., Ng, A.Y., Jordan, M.I.: Latent dirichlet allocation. J. Mach. Learn. Res. 3, 993–1022 (2003)
Cao, L.: In-depth behavior understanding and use: the behavior informatics approach. Information Science 180, 3067–3085 (2010)
Chen, Y., Tsai, F.S., Chan, K.L.: Machine learning techniques for business blog search and mining. Expert Syst. Appl. 35(3), 581–590 (2008)
Cohn, D., Hofmann, T.: The missing link – a probabilistic model of document content and hypertext connectivity. In: Advances in Neural Information Processing Systems, vol. 13, pp. 430–436 (2001)
Erosheva, E., Fienberg, S., Lafferty, J.: Mixed-membership models of scientific publications. Proceedings of the National Academy of Sciences of the United States of America 101(suppl. 1), 5220–5227 (2004)
Guo, Z., Zhu, S., Chi, Y., Zhang, Z., Gong, Y.: A latent topic model for linked documents. In: SIGIR 2009: Proceedings of the 32nd International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 720–721. ACM, New York (2009)
Liang, H., Tsai, F.S., Kwee, A.T.: Detecting novel business blogs. In: ICICS 2009: Proceedings of the 7th International Conference on Information, Communications and Signal Processing (2009)
Liu, Y., Niculescu-Mizil, A., Gryc, W.: Topic-link lda: joint models of topic and author community. In: ICML 2009: Proceedings of the 26th Annual International Conference on Machine Learning, pp. 665–672. ACM, New York (2009)
Macdonald, C., Ounis, I.: The TREC Blogs06 collection: Creating and analysing a blog test collection. Tech. rep., Dept of Computing Science, University of Glasgow (2006)
Nallapati, R., Cohen, W.: Link-PLSA-LDA: A new unsupervised model for topics and influence of blogs. In: Proceedings of the International Conference on Weblogs and Social Media (ICWSM). Association for the Advancement of Artificial Intelligence (2008)
Rosen-Zvi, M., Griffiths, T., Steyvers, M., Smyth, P.: The author-topic model for authors and documents. In: AUAI 2004: Proceedings of the 20th Conference on Uncertainty in Artificial Intelligence, pp. 487–494. AUAI Press, Arlington (2004)
Steyvers, M., Smyth, P., Rosen-Zvi, M., Griffiths, T.: Probabilistic author-topic models for information discovery. In: KDD 2004: Proceedings of the Tenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 306–315. ACM, New York (2004)
Tsai, F.S.: A data-centric approach to feed search in blogs. International Journal of Web Engineering and Technology (2012)
Tsai, F.S.: Dimensionality reduction techniques for blog visualization. Expert Systems With Applications 38(3), 2766–2773 (2011)
Tsai, F.S., Chan, K.L.: Detecting Cyber Security Threats in Weblogs using Probabilistic Models. In: Yang, C.C., Zeng, D., Chau, M., Chang, K., Yang, Q., Cheng, X., Wang, J., Wang, F.-Y., Chen, H. (eds.) PAISI 2007. LNCS, vol. 4430, pp. 46–57. Springer, Heidelberg (2007)
Tsai, F.S., Chan, K.L.: Dimensionality reduction techniques for data exploration. In: 2007 6th International Conference on Information, Communications and Signal Processing, ICICS, pp. 1568–1572 (2007)
Tsai, F.S., Chan, K.L.: Redundancy and novelty mining in the business blogosphere. The Learning Organization 17(6), 490–499 (2010)
Tsai, F.S., Chen, Y., Chan, K.L.: Probabilistic Techniques for Corporate Blog Mining. In: Washio, T., Zhou, Z.-H., Huang, J.Z., Hu, X., Li, J., Xie, C., He, J., Zou, D., Li, K.-C., Freire, M.M. (eds.) PAKDD 2007. LNCS (LNAI), vol. 4819, pp. 35–44. Springer, Heidelberg (2007)
Tsai, F.S., Han, W., Xu, J., Chua, H.C.: Design and Development of a Mobile Peer-to-Peer Social Networking Application. Expert Syst. Appl. 36(8), 11077–11087 (2009)
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Tsai, F.S. (2012). Blogger-Link-Topic Model for Blog Mining. In: Cao, L., Huang, J.Z., Bailey, J., Koh, Y.S., Luo, J. (eds) New Frontiers in Applied Data Mining. PAKDD 2011. Lecture Notes in Computer Science(), vol 7104. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28320-8_3
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DOI: https://doi.org/10.1007/978-3-642-28320-8_3
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