Mining Community-Level Influence in Microblogging Network: A Case Study on Sina Weibo

<table class="table-group" id="tab2"><tr><td><table class="table"><tr><td class="thead-hr" colspan="2"><hr/></td></tr><tr class="thead"><td class="align_left">Features</td><td class="align_left">Description</td></tr><tr><td class="thead-hr" colspan="2"><hr/></td></tr><tr><td class="align_left">ThemeID</td><td class="align_left">Theme information ID</td></tr><tr><td class="align_left">ThemeFromID</td><td class="align_left">Source ID of theme information</td></tr><tr><td class="align_left">ProNum</td><td class="align_left">Number of processes</td></tr><tr><td class="align_left">ThemeClass</td><td class="align_left">Theme information class</td></tr><tr><td class="align_left">PTime</td><td class="align_left">Post time of theme information</td></tr><tr class="table-tr"><td colspan="2"><hr class="tbody-hr"/></td></tr></table></td></tr></table>

Data structure and description of the user theme information (microblogs).

Complexity

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Table 2

Table 2: Mining Community-Level Influence in Microblogging Network: A Case Study on Sina Weibo 