Abstract
Topic evolutionary analysis on microblog feeds can help reveal users’ interests and public concerns in a global perspective. However, it is not easy to capture the evolutionary patterns since the semantic coherence is usually difficult to be expressed and the timeline structure is always intractable to be organized. In this paper, we propose a novel strategy, in which a coherent topic hierarchy is designed to deal with these challenges. First, we incorporate the sparse biterm topic model to extract some coherent topics from microblog feeds. Then the topology of these topics is constructed by the basic Bayesian rose tree combined with topic similarity. Finally, we devise a cross-tree random walk with restart model to bond each pair of sequential trees into a timeline hierarchy. Experimental results on microblog datasets demonstrate that the coherent topic hierarchy is capable of providing meaningful topic interpretations, achieving high clustering performance, as well as presenting motivated patterns for topic evolutionary analysis.
This research is supported by the Natural Science Foundation of China(No.61472291, No.61272110, No.61272275, No.71420107026, No.164659), and the China Postdoctoral Science Foundation under contract No.2014M562070.
This is a preview of subscription content, log in via an institution to check access.
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
Blei, D., Ng, A., Jordan, M.: Latent Dirichlet allocation. The Journal of Machine Learning Research 3, 993–1022 (2003)
Blei, D., Lafferty, J.: Dynamic topic models. In: ICML 2006, pp. 113–120. ACM (2006)
AlSumait, L., Barbar, D., Domeniconi, C.: Online lda: adaptive topic models for mining text streams with applications to topic detection and tracking. In: ICDM 2008, pp. 3–12. IEEE (2008)
Long, R., Wang, H., Chen, Y., Jin, O., Yu, Y.: Towards effective event detection, tracking and summarization on microblog data. In: Wang, H., Li, S., Oyama, S., Hu, X., Qian, T. (eds.) WAIM 2011. LNCS, vol. 6897, pp. 652–663. Springer, Heidelberg (2011)
Yang, X., Ghoting, A., Ruan, Y., et al.: A framework for summarizing and analyzing twitter feeds. In: KDD 2012, pp. 370–378. ACM (2012)
Shou, L., Wang, Z., Chen, K., et al.: Sumblr: continuous summarization of evolving tweet streams. In: SIGIR 2013, pp. 533–542. ACM (2013)
Wang, X., Liu, S., Song, Y., et al.: Mining evolutionary multi-branch trees from text streams. In: KDD 2013, pp. 722–730. ACM (2013)
Zhu, X., Ming, Z., Hao, Y., et al.: Customized organization of social media contents using focused topic hierarchy. In: CIKM 2014, pp. 1509–1518. ACM (2014)
Yan, X., Guo, J., Lan, Y., et al.: A biterm topic model for short texts. In: WWW 2013, pp. 1445–1456. ACM (2013)
Blundell, C., Teh, Y., Heller, K.: Bayesian rose trees. In: UAI 2010 (2010). arXiv:1203.3468
Wang, X., McCallum, A.: Topics over time: a non-Markov continuous-time model of topical trends. In: KDD 2006, pp. 424–433. ACM (2006)
Zhang, J., Song, Y., Zhang, C., et al.: Evolutionary hierarchical Dirichlet processes for multiple correlated time-varying corpora. In: KDD 2010, pp. 1079–1088. ACM (2010)
Wang, Y., Agichtein, E., Benzi, M.: Tm-lda: efficient online modeling of latent topic transitions in social media. In: KDD 2012, pp. 123–131. ACM (2012)
Chang, J., Gerrish, S., Wang, C., et al.: Reading tea leaves: how humans interpret topic models. In: NIPS 2009, pp. 288–296. MIT Press (2009)
Chen, Z., Mukherjee, A., Liu, B., et al.: Discovering coherent topics using general knowledge. In: CIKM 2013, pp. 209–218. ACM (2013)
Lin, T., Tian, W., Mei, Q., et al.: The dual-sparse topic model: mining focused topics and focused terms in short text. In: WWW 2014, pp. 539–550. ACM (2014)
Lin, C., Lin, C., Li, J., et al.: Generating event storylines from microblogs. In: CIKM 2012, pp. 175–184. ACM (2012)
Zhu, X., Ming, Z., Zhu, X., et al.: Topic hierarchy construction for the organization of multi-source user generated contents. In: SIGIR 2013, pp. 233–242. ACM (2013)
Tong, H., Faloutsos, C., Pan, J.: Fast random walk with restart and its applications. In: ICDM 2006, pp. 613–622. IEEE (2006)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer International Publishing Switzerland
About this paper
Cite this paper
Zhu, J. et al. (2015). Coherent Topic Hierarchy: A Strategy for Topic Evolutionary Analysis on Microblog Feeds. In: Dong, X., Yu, X., Li, J., Sun, Y. (eds) Web-Age Information Management. WAIM 2015. Lecture Notes in Computer Science(), vol 9098. Springer, Cham. https://doi.org/10.1007/978-3-319-21042-1_6
Download citation
DOI: https://doi.org/10.1007/978-3-319-21042-1_6
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-21041-4
Online ISBN: 978-3-319-21042-1
eBook Packages: Computer ScienceComputer Science (R0)