Chinese Microblog Sentiment Detection Based on CNN-BiGRU and Multihead Attention Mechanism

<table class="table-group" id="tab2"><tr><td><table class="table"><tr><td class="thead-hr" colspan="5"><hr/></td></tr><tr class="thead"><td class="align_left"> </td><td class="align_center">Training dataset</td><td class="align_center">Testing dataset</td><td class="align_center">Val. dataset</td><td class="align_center">Total number of SMS</td></tr><tr><td class="thead-hr" colspan="5"><hr/></td></tr><tr><td class="align_left">Positive</td><td class="align_center">10000</td><td class="align_center">39994</td><td class="align_center">10000</td><td class="align_center">59994</td></tr><tr><td class="align_left">Negative</td><td class="align_center">10000</td><td class="align_center">39994</td><td class="align_center">10000</td><td class="align_center">59994</td></tr><tr><td class="align_left">Percentage</td><td class="align_center">80%</td><td class="align_center">10%</td><td class="align_center">10%</td><td class="align_center">100%</td></tr><tr class="table-tr"><td colspan="5"><hr class="tbody-hr"/></td></tr></table></td></tr></table>

<div>The distribution of the training set, test set, and validation set of the dataset.</div>

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tab2

Table 2

Table 2: Chinese Microblog Sentiment Detection Based on CNN-BiGRU and Multihead Attention Mechanism 