News Comments: Exploring, Modeling, and Online Prediction

Online news agents provide commenting facilities for their readers to express their opinions or sentiments with regards to news stories. The number of user supplied comments on a news article may be indicative of its importance, interestingness, or impact. We explore the news comments space, and compare the log-normal and the negative binomial distributions for modeling comments from various news agents. These estimated models can be used to normalize raw comment counts and enable comparison across different news sites. We also examine the feasibility of online prediction of the number of comments, based on the volume observed shortly after publication. We report on solid performance for predicting news comment volume in the long run, after short observation. This prediction can be useful for identifying news stories with the potential to “take off,” and can be used to support front page optimization for news sites.

[1]  Virgílio A. F. Almeida,et al.  Traffic Characteristics and Communication Patterns in Blogosphere , 2006, ICWSM.

[2]  Gilad Mishne,et al.  A Study of Blog Search , 2006, ECIR.

[3]  Maliha S. Nash,et al.  Handbook of Parametric and Nonparametric Statistical Procedures , 2001, Technometrics.

[4]  Vicenç Gómez,et al.  Description and Prediction of Slashdot Activity , 2007, 2007 Latin American Web Conference (LA-WEB 2007).

[5]  Josep Blat,et al.  Homogeneous Temporal Activity Patterns in a Large Online Communication Space , 2007, SAW.

[6]  Bernardo A. Huberman,et al.  Predicting the popularity of online content , 2008, Commun. ACM.

[7]  SzaboGabor,et al.  Predicting the popularity of online content , 2010 .

[8]  Kavé Salamatian,et al.  Understanding the characteristics of online commenting , 2008, CoNEXT '08.

[9]  Munmun De Choudhury,et al.  What makes conversations interesting?: themes, participants and consequences of conversations in online social media , 2009, WWW '09.

[10]  Fang Wu,et al.  Novelty and collective attention , 2007, Proceedings of the National Academy of Sciences.

[11]  M. de Rijke,et al.  Predicting the volume of comments on online news stories , 2009, CIKM.

[12]  Maarten de Rijke,et al.  Extracting the discussion structure in comments on news-articles , 2007, WIDM '07.

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

[14]  Peter Ingwersen,et al.  Developing a Test Collection for the Evaluation of Integrated Search , 2010, ECIR.

[15]  Gilad Mishne,et al.  Capturing Global Mood Levels using Blog Posts , 2006, AAAI Spring Symposium: Computational Approaches to Analyzing Weblogs.

[16]  Deborah S. Chung,et al.  Interactive Features of Online Newspapers: Identifying Patterns and Predicting Use of Engaged Readers , 2008, J. Comput. Mediat. Commun..