Free Online Productivity Tools
i2Speak
i2Symbol
i2OCR
iTex2Img
iWeb2Print
iWeb2Shot
i2Type
iPdf2Split
iPdf2Merge
i2Bopomofo
i2Arabic
i2Style
i2Image
i2PDF
iLatex2Rtf
Sci2ools
ECIR
2010
Springer
2010
Springer
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.
Real-time TrafficECIR 2010 | Information Technology | Negative Binomial Distributions | Raw Comment Counts | User Supplied Comments |
Related Content
| Added | 29 Oct 2010 |
| Updated | 29 Oct 2010 |
| Type | Conference |
| Year | 2010 |
| Where | ECIR |
| Authors | Manos Tsagkias, Wouter Weerkamp, Maarten de Rijke |
Comments (0)
Researcher Info
|
