In recent years, users spend more time on surfing the social networking than ever before. How to make the information spread rapidlywhen facing vast amounts of information?Scholars have conducted information dissemination in social networking. On the basis of previous research, the authors divide posts into popular posts and ordinary posts and then use the linear regression model to predict the replies at specified time. After comparing the difference between two types of posts, the authors concludethat ordinary posts could become popular posts if the posts could maintain a large number of replies within former five hours and increase replies by making use of community mechanism. This conclusion provides a reasonable proposal for enterprises and administrators to identify andrecommendpopular posts.
Chen, Jingwen; Liao, Shumeng; and Yin, Yuan, "Analyze the Trend of Post Replies Based on Linear Regression Model-----take Tianyawebsiteas examples" (2015). WHICEB 2015 Proceedings. 68.