Two Applications of Clustering Techniques to Twitter: Community Detection and Issue Extraction

<table class="table-group" id="tab2"><tr><td><table class="table"><tr><td class="thead-hr" colspan="3"><hr/></td></tr><tr class="thead"><td align="left"> </td><td align="center">Original Louvain algorithm</td><td align="center">Partitioned Louvain algorithm</td></tr><tr><td class="thead-hr" colspan="3"><hr/></td></tr><tr><td align="left">Processing</td><td align="center">N/A</td><td align="center">16 hours </td></tr><tr><td align="left">Time </td><td align="center">(&gt;72 hours)</td><td align="center">38 minutes</td></tr><tr><td align="left">Modularity</td><td align="center">N/A</td><td align="center">0.343</td></tr><tr class="table-tr"><td colspan="3"><hr class="tbody-hr"/></td></tr></table></td></tr></table>

Experimental results on <i>Twitter</i> data.

Discrete Dynamics in Nature and Society

tab2

Table 2

Table 2: Two Applications of Clustering Techniques to Twitter: Community Detection and Issue Extraction 