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http://dx.doi.org/10.3745/KIPSTD.2012.19D.1.113

A Model to Predict Popularity of Internet Posts on Internet Forum Sites  

Lee, Yun-Jung (부산대학교 U-Port 정보기술공동사업단)
Jung, In-Jun (부산대학교 컴퓨터공학과)
Woo, Gyun (부산대학교 컴퓨터공학과)
Publication Information
The KIPS Transactions:PartD / v.19D, no.1, 2012 , pp. 113-120 More about this Journal
Abstract
Today, Internet users can easily create and share the digital contents with others through various online content sharing services such as YouTube. So, many portal sites are flooded with lots of user created contents (UCC) in various media such as texts and videos. Estimating popularity of UCC is a crucial concern to both users and the site administrators. This paper proposes a method to predict the popularity of Internet articles, a kind of UCC, using the dynamics of the online contents themselves. To analyze the dynamics, we regarded the access counts of Internet posts as the popularity of them and analyzed the variation of the access counts. We derived a model to predict the popularity of a post represented by the time series of access counts, which is based on an exponential function. According to the experimental results, the difference between the actual access counts and the predicted ones is not more than 10 for 20,532 posts, which cover about 90.7% of the test set.
Keywords
Social Media; Internet Discussion Board; Online Contents; Predicting Popularity; Dynamics of Online Contents;
Citations & Related Records
Times Cited By KSCI : 2  (Citation Analysis)
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