Extracting the discussion structure in comments on news-articles
Proceedings of the 9th annual ACM international workshop on Web information and data management
Description and Prediction of Slashdot Activity
LA-WEB '07 Proceedings of the 2007 Latin American Web Conference
Proceedings of the 18th international conference on World wide web
Handbook of Parametric and Nonparametric Statistical Procedures
Handbook of Parametric and Nonparametric Statistical Procedures
Understanding the characteristics of online commenting
CoNEXT '08 Proceedings of the 2008 ACM CoNEXT Conference
Predicting the volume of comments on online news stories
Proceedings of the 18th ACM conference on Information and knowledge management
ECIR'06 Proceedings of the 28th European conference on Advances in Information Retrieval
Proceedings of the ACM 2011 conference on Computer supported cooperative work
Predicting the popularity of online articles based on user comments
Proceedings of the International Conference on Web Intelligence, Mining and Semantics
A straw shows which way the wind blows: ranking potentially popular items from early votes
Proceedings of the fifth ACM international conference on Web search and data mining
Recent developments in information retrieval
ECIR'2010 Proceedings of the 32nd European conference on Advances in Information Retrieval
Care to comment?: recommendations for commenting on news stories
Proceedings of the 21st international conference on World Wide Web
Predicting IMDB movie ratings using social media
ECIR'12 Proceedings of the 34th European conference on Advances in Information Retrieval
Predicting responses to microblog posts
NAACL HLT '12 Proceedings of the 2012 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
Diversifying user comments on news articles
WISE'12 Proceedings of the 13th international conference on Web Information Systems Engineering
A peek into the future: predicting the evolution of popularity in user generated content
Proceedings of the sixth ACM international conference on Web search and data mining
Ranking News Articles Based on Popularity Prediction
ASONAM '12 Proceedings of the 2012 International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2012)
Using temporal bursts for query modeling
Information Retrieval
Hi-index | 0.00 |
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.