Title :
Digging Digg: Comment Mining, Popularity Prediction, and Social Network Analysis
Author :
Jamali, Salman ; Rangwala, Huzefa
Author_Institution :
Dept. of Comput. Sci. & Eng., George Mason Univ., Fairfax, VA, USA
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.
Keywords :
data mining; entropy; feature extraction; pattern classification; regression analysis; social networking (online); Digg; behavioral characteristics; classification framework; comment mining; coparticipation network; entropy measure; feature extraction; implicit network analysis; popularity prediction; regression framework; social network analysis; Collaborative work; Computer science; Discussion forums; Entropy; Information analysis; Information systems; Particle measurements; Pattern analysis; Social network services; Yarn; Comment Mining; Egonet Analysis; Popularity Prediction; Social Bookmarking; Social Network Analysis;
Conference_Titel :
Web Information Systems and Mining, 2009. WISM 2009. International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-0-7695-3817-4
DOI :
10.1109/WISM.2009.15