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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Jamali, S. Rangwala, H. |
| Copyright Year | 2009 |
| Abstract | Using comment information available from Digg we define a co-participation network between users. We focus on the analysis of this implicit network, and study the behavioral characteristics of users. Using an entropy measure, we infer that users at Digg are not highly focused and participate across a wide range of topics. We also use the comment data and social network derived features to predict the popularity of online content linked at Digg using a classification and regression framework. We show promising results for predicting the popularity scores even after limiting our feature extraction to the first few hours of comment activity that follows a Digg submission. |
| Starting Page | 32 |
| Ending Page | 38 |
| File Size | 3593989 |
| Page Count | 7 |
| File Format | |
| ISBN | 9780769538174 |
| DOI | 10.1109/WISM.2009.15 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2009-11-07 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Social Network Analysis Comment Mining Discussion forums Social network services Social Bookmarking Entropy Yarn Information analysis Information systems Computer science Egonet Analysis Collaborative work Particle measurements Popularity Prediction Pattern analysis |
| Content Type | Text |
| Resource Type | Article |
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