Modelling the Latent Semantics of Diffusion Sources in Information Cascade Prediction

<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">Dataset</td><td class="align_center"># Users</td><td class="align_center"># Diffusion sources</td><td class="align_center"># Cascades</td><td class="align_center">Average cascade size</td></tr><tr><td class="thead-hr" colspan="5"><hr/></td></tr><tr><td class="align_left">Twitter</td><td class="align_center">5942</td><td class="align_center">204</td><td class="align_center">569</td><td class="align_center">17.0422</td></tr><tr><td class="align_left">Weibo</td><td class="align_center">8183</td><td class="align_center">6541</td><td class="align_center">39029</td><td class="align_center">21.9078</td></tr><tr class="table-tr"><td colspan="5"><hr class="tbody-hr"/></td></tr></table></td></tr></table>

<div>Statistics of evaluation datasets.</div>

Computational Intelligence and Neuroscience

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Table 1

Table 1: Modelling the Latent Semantics of Diffusion Sources in Information Cascade Prediction 