DocumentCode
2897819
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
fYear
2009
fDate
7-8 Nov. 2009
Firstpage
32
Lastpage
38
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;
fLanguage
English
Publisher
ieee
Conference_Titel
Web Information Systems and Mining, 2009. WISM 2009. International Conference on
Conference_Location
Shanghai
Print_ISBN
978-0-7695-3817-4
Type
conf
DOI
10.1109/WISM.2009.15
Filename
5368318
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