Table 6.

Pearson's correlation statistics among six influence algorithms namely proposed WCI measure, TweetRank, Popularity, PageRank, Out-Degree, and Eigenvector for both the generated Twitter datasets is presented. A total of 15 potential pairs are shown.

Algorithms	${\overrightarrow{G}}_{\#\mathit{Delh}\mathit{Viol}\mathit{ence}}$	${\overrightarrow{G}}_{\#\mathit{Coro}\mathit{navi}\mathit{rusP}\mathit{ande}\mathit{mic}}$
Proposed WCI & TweetRank	0.686	0.257
Proposed WCI & Popularity	0.709	0.919
Proposed WCI & PageRank	0.017	0.358
Proposed WCI & Out-Degree	0.003	$-0.046$
Proposed WCI & Eigenvector	$-0.035$	0.184
TweetRank & Popularity	0.113	0.083
TweetRank & PageRank	0.113	0.017
TweetRank & Out-Degree	0.046	0.046
TweetRank & Eigenvector	$-0.031$	0.03
Popularity & PageRank	0.025	0.221
Popularity & Out-Degree	$-0.051$	$-0.07$
Popularity & Eigenvector	$-0.033$	0.09
PageRank & Out-Degree	0.012	0.029
PageRank & Eigenvector	0.525	0.511
Out-Degree & Eigenvector	$-0.021$	0.001