BBS Topic's Hotness Forecast Based on Back-Propagation Neural Network

Online hot topic detection is a significant research field in web data mining, which can help people make policy decision or benefit to people's daily life. Actually, in recent years more and more hot topics are arising from BBS, often referred as online forum. BBS provide a communication platform for people to discuss and express their views. It's obvious that forecasting the hotness topics on BBS is important and meaningful. In this paper we present an approach to predict the hotness of topics based on BPNN (Back-Propagation Neural Network). Text sentiment internet user's attention and hotspot relative have been considered to forecast the hotness of topics. At the last the experiment results over SINA reading forum show our approach is effective.