What's Worthy of Comment? Content and Comment Volume in Political Blogs

In this paper we aim to model the relationship be- tween the text of a political blog post and the comment volume—that is, the total amount of response—that a post will receive. We seek to accurately identify which posts will attract a high-volume response, and also to gain insight about the community of readers and their interests. We design and evaluate variations on a latent- variable topic model that links text to comment volume.

[1]  Thomas L. Griffiths,et al.  Probabilistic Topic Models , 2007 .

[2]  C. Elkan,et al.  Topic Models , 2008 .

[3]  Eric P. Xing,et al.  MedLDA: maximum margin supervised topic models for regression and classification , 2009, ICML '09.

[4]  Danielle S. McNamara,et al.  Handbook of latent semantic analysis , 2007 .

[5]  Dragomir R. Radev,et al.  An Automated Method of Topic-Coding Legislative Speech Over Time with Application to the 105th-108th U.S. Senate , 2006 .

[6]  Christian P. Robert,et al.  Monte Carlo Statistical Methods , 2005, Springer Texts in Statistics.

[7]  David M. Blei,et al.  Supervised Topic Models , 2007, NIPS.

[8]  Ramesh Nallapati,et al.  Labeled LDA: A supervised topic model for credit attribution in multi-labeled corpora , 2009, EMNLP.

[9]  G. Casella,et al.  Statistical Inference , 2003, Encyclopedia of Social Network Analysis and Mining.

[10]  Trevor Hastie,et al.  Regularization Paths for Generalized Linear Models via Coordinate Descent. , 2010, Journal of statistical software.

[11]  Noah A. Smith,et al.  Predicting Response to Political Blog Posts with Topic Models , 2009, NAACL.

[12]  Mark Steyvers,et al.  Finding scientific topics , 2004, Proceedings of the National Academy of Sciences of the United States of America.

[13]  Andrew McCallum,et al.  Topic Models Conditioned on Arbitrary Features with Dirichlet-multinomial Regression , 2008, UAI.

[14]  Justin Grimmer,et al.  A Bayesian Hierarchical Topic Model for Political Texts: Measuring Expressed Agendas in Senate Press Releases , 2010, Political Analysis.

[15]  Gilad Mishne,et al.  Leave a Reply: An Analysis of Weblog Comments , 2006 .

[16]  Gregor Heinrich.  Parameter estimation for text analysis , 2009 .

[17]  J. Lafferty,et al.  Mixed-membership models of scientific publications , 2004, Proceedings of the National Academy of Sciences of the United States of America.

[18]  Michael I. Jordan,et al.  Latent Dirichlet Allocation , 2001, J. Mach. Learn. Res..