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http://dx.doi.org/10.5392/JKCA.2011.11.10.019

Predicting the Popularity of Post Articles with Virtual Temperature in Web Bulletin  

Kim, Su-Do (부산대학교 U-Port정보기술산학공동사업단)
Kim, So-Ra (부산대학교 컴퓨터공학과)
Cho, Hwan-Gue (부산대학교 컴퓨터공학과)
Publication Information
The Journal of the Korea Contents Association / v.11, no.10, 2011 , pp. 19-29 More about this Journal
Abstract
A Blog provides commentary, news, or content on a particular subject. The important part of many blogs is interactive format. Sometimes, there is a heated debate on a topic and any article becomes a political or sociological issue. In this paper, we proposed a method to predict the popularity of an article in advance. First, we used hit count as a factor to predict the popularity of an article. We defined the saturation point and derived a model to predict the hit count of the saturation point by a correlation coefficient of the early hit count and hit count of the saturation point. Finally, we predicted the virtual temperature of an article using 4 types(explosive, hot, warm, cold). We can predict the virtual temperature of Internet discussion articles using the hit count of the saturation point with more than 70% accuracy, exploiting only the first 30 minutes' hit count. In the hot, warm, and cold categories, we can predict more than 86% accuracy from 30 minutes' hit count and more than 90% accuracy from 70 minutes' hit count.
Keywords
Prediction; Popularity; Web Blog; Social Network;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
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