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Table 2 Structural properties of the 12 largest communities

From: Sentiment leaning of influential communities in social networks

k

Name

Users

Unique

I in (C k )

I out (C k )

\(\frac {I_{\textit {out}}(C_{k})}{I_{\textit {in}}(C_{k})}\)

H H I(C k )

   

tweets

    

1

Env 1

366,979

625,280

1,546,998

787,139

0.509

0.037

2

Env 2

324,518

561,659

2,189,373

796,861

0.364

0.034

3

News 1

275,172

325,867

1,160,347

385,355

0.332

0.035

4

Humor

272,780

12,971

330,897

150,148

0.454

0.065

5

News 2

254,159

44,587

363,539

307,039

0.845

0.036

6

Skeptic

160,257

236,618

983,672

132,509

0.135

0.029

7

India

96,158

32,981

311,754

37,849

0.121

0.045

8

Celebrity

92,434

13,480

174,105

36,414

0.209

0.158

9

News 3

91,446

95,415

274,704

91,323

0.332

0.032

10

Env 3

83,259

180,210

707,292

187,576

0.265

0.030

11

Other

65,363

13,697

115,709

41,309

0.357

0.031

12

Env 4

53,847

29,863

105,608

19,796

0.187

0.104

  1. Community influence I(C) is split into I in (C) and I out (C), intra- and inter-community influence, respectively. H H I(C) is the Herfindahl-Hirshmann index of the intra-community influence