Abstract
The Time Pre-discretized model is firstly adopted to extract web news topic, then a model of topic content evolution is adopted based on the analysis of topic clusters, on which basis a quantification method of topic content is proposed. Experiments on the data sets from social web media find a Pearson correlation coefficient (PCC) of 0.74 between the sequence of topic intensity and that of topic content complexity based on the above quantification method, and a more than 71.5% chance of the simultaneous increase/decrease is observed, showing the “increase or decrease together” law of topic intensity evolution based on topic content evolution.
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Li, Z., Yin, Z., Li, Q. (2018). Study on Topic Intensity Evolution Law of Web News Topic Based on Topic Content Evolution. In: Sun, X., Pan, Z., Bertino, E. (eds) Cloud Computing and Security. ICCCS 2018. Lecture Notes in Computer Science(), vol 11068. Springer, Cham. https://doi.org/10.1007/978-3-030-00021-9_62
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DOI: https://doi.org/10.1007/978-3-030-00021-9_62
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