Evolutionary Prediction of Nonstationary Event Popularity Dynamics of Weibo Social Network Using Time-Series Characteristics

<table class="table-group" id="tab1"><tr><td><table class="table"><tr><td class="thead-hr" colspan="5"><hr/></td></tr><tr class="thead"><td class="align_left">Datasets</td><td class="align_center">Classification</td><td class="align_center">Users</td><td class="align_center">Followers</td><td class="align_center">Forwarding statistic</td></tr><tr><td class="thead-hr" colspan="5"><hr/></td></tr><tr><td class="align_left">Chengdu-Driver</td><td class="align_center">Social</td><td class="align_center">7259</td><td class="align_center">135455</td><td class="align_center">159711</td></tr><tr><td class="align_left">Baihe</td><td class="align_center">Entertainment</td><td class="align_center">1533</td><td class="align_center">1395880</td><td class="align_center">536674</td></tr><tr><td class="align_left">THAAD</td><td class="align_center">International news</td><td class="align_center">5532</td><td class="align_center">1891069</td><td class="align_center">2130227</td></tr><tr class="table-tr"><td colspan="5"><hr class="tbody-hr"/></td></tr></table></td></tr></table>

<div>Details about the three datasets of hot public opinion events.</div>

Discrete Dynamics in Nature and Society

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Table 1

Table 1: Evolutionary Prediction of Nonstationary Event Popularity Dynamics of Weibo Social Network Using Time-Series Characteristics 