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社交网络中新闻趋势的预测分析

Predicting News Trend in the Social Network

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【作者】 路荣张旸杨青

【Author】 LU Rong,ZHANG Yang,YANG Qing(National Laboratory of Pattern Recognition,Institute of Automation,Chinese Academy of Sciences,Beijing 100190,China)

【机构】 中国科学院自动化研究所模式识别国家重点实验室

【摘要】 新闻在社交网络平台中的发展趋势,可以用其在该网络中出现的频率的移动平均值来跟踪。该文利用两条不同时间周期的移动平均值来分别跟踪新闻的相对短期趋势和相对长期趋势,并定义这两种趋势的差值为该新闻趋势发展的趋势动量。当趋势动量值为正,该新闻将有更加热门的可能,反之,则表明该新闻的关注度正在降低。而该趋势动量值本身的大小变化,也同样能为新闻趋势的变化提供预测。实验证明,该文的方法简单有效,能很好地对社交网络中新闻未来可能发展趋势做出即时、准确的预测。

【Abstract】 The trend of news event in the social network can be tracked by the moving average of its frequency of occurrence.This paper presets a novel method to track the shorter trend and the longer trend of news by the moving average lines of two different sized time-window are adopted.The momentum of the news trend is defined as the difference between the shorter moving average and the longer moving average.When the value of the momentum is positive,the news are more likely to get hotter,and vice versa.Moreover,the change of the momentum value itself provides an even earlier indicator of the news trend.Experimental results show proves the proposed method is simple and effective in predicting the news trend in time and accurately.

  • 【文献出处】 中文信息学报 ,Journal of Chinese Information Processing , 编辑部邮箱 ,2012年06期
  • 【分类号】TP391.1
  • 【被引频次】7
  • 【下载频次】348
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